Part1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
      "  from pandas.core import datetools\n"
     ]
    }
   ],
   "source": [
    "from thermo.chemical import Chemical\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from fancyimpute import IterativeSVD\n",
    "import statsmodels.formula.api as sm\n",
    "import statsmodels.api as sma\n",
    "\n",
    "matplotlib.style.use('ggplot')\n",
    "\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "comps = open('compounds.txt','r')\n",
    "\n",
    "f =  open('features_dl.csv', 'w')\n",
    "w = csv.writer(f)\n",
    "w.writerow(['Name','MF', 'MW','CPG','CPL','TB','TMelt','TT','TC','PC','VC','RHOC','PSAT','HVAP','HFUS', 'HF', 'Vm', 'Visc'])\n",
    "\n",
    "for comp in comps:\n",
    "    try:\n",
    "        name = comp.strip('\\n')\n",
    "        name = name.strip('\\t')\n",
    "        c = Chemical(name)\n",
    "        data = [name,c.formula,c.MW,c.Cpg,c.Cpl,c.Tb, c.Tm,c.Tt,c.Tc,c.Pc,c.Vc,c.rhoc,c.Psat, c.Hvap, c.Hfus, c.Hf, c.Vm, c.mu]\n",
    "        w.writerow(data)\n",
    "    except Exception as e:\n",
    "        pass\n",
    "\n",
    "f.close()\n",
    "comps.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MF</th>\n",
       "      <th>MW</th>\n",
       "      <th>CPG</th>\n",
       "      <th>CPL</th>\n",
       "      <th>TB</th>\n",
       "      <th>TMelt</th>\n",
       "      <th>TT</th>\n",
       "      <th>TC</th>\n",
       "      <th>PC</th>\n",
       "      <th>VC</th>\n",
       "      <th>RHOC</th>\n",
       "      <th>PSAT</th>\n",
       "      <th>HVAP</th>\n",
       "      <th>HFUS</th>\n",
       "      <th>HF</th>\n",
       "      <th>Vm</th>\n",
       "      <th>Visc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1,3-Cyclopentadiene</td>\n",
       "      <td>C5H6</td>\n",
       "      <td>66.10114</td>\n",
       "      <td>1140.819957</td>\n",
       "      <td>1802.292349</td>\n",
       "      <td>314.15</td>\n",
       "      <td>182.05</td>\n",
       "      <td>182.05</td>\n",
       "      <td>500.0</td>\n",
       "      <td>4699960.0</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>284.918707</td>\n",
       "      <td>59226.323229</td>\n",
       "      <td>405076.739586</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130800.0</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cyclopentene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1194.705857</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>317.35</td>\n",
       "      <td>138.15</td>\n",
       "      <td>138.13</td>\n",
       "      <td>506.5</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>278.028653</td>\n",
       "      <td>50440.182509</td>\n",
       "      <td>408584.752841</td>\n",
       "      <td>49326.878950</td>\n",
       "      <td>32930.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2-Methyl-1,3-butadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1508.531750</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>307.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>483.3</td>\n",
       "      <td>3739997.0</td>\n",
       "      <td>0.000266</td>\n",
       "      <td>256.079023</td>\n",
       "      <td>73379.808091</td>\n",
       "      <td>361991.935213</td>\n",
       "      <td>72375.450365</td>\n",
       "      <td>75750.0</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1,4-Pentadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1443.650821</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>299.05</td>\n",
       "      <td>125.15</td>\n",
       "      <td>125.15</td>\n",
       "      <td>478.0</td>\n",
       "      <td>3789555.0</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>246.800797</td>\n",
       "      <td>97975.483765</td>\n",
       "      <td>360428.662730</td>\n",
       "      <td>89845.386660</td>\n",
       "      <td>106380.0</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1-Pentyne</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1507.232005</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>313.05</td>\n",
       "      <td>167.15</td>\n",
       "      <td>167.15</td>\n",
       "      <td>493.4</td>\n",
       "      <td>4053000.0</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>245.025252</td>\n",
       "      <td>58084.265066</td>\n",
       "      <td>413392.656845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144350.0</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cyclopentane</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1183.596267</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>322.35</td>\n",
       "      <td>179.15</td>\n",
       "      <td>179.70</td>\n",
       "      <td>511.7</td>\n",
       "      <td>4510000.0</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>270.783398</td>\n",
       "      <td>42319.067142</td>\n",
       "      <td>404672.441280</td>\n",
       "      <td>8697.772372</td>\n",
       "      <td>-77240.0</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2-Methyl-2-butene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1497.059793</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>311.65</td>\n",
       "      <td>139.15</td>\n",
       "      <td>139.42</td>\n",
       "      <td>470.0</td>\n",
       "      <td>3420000.0</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>234.558194</td>\n",
       "      <td>62147.076804</td>\n",
       "      <td>388900.424471</td>\n",
       "      <td>108365.688571</td>\n",
       "      <td>-42550.0</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>0.000206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3-Methyl-1-butene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1632.299430</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>293.25</td>\n",
       "      <td>104.90</td>\n",
       "      <td>104.72</td>\n",
       "      <td>452.7</td>\n",
       "      <td>3530000.0</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>230.019351</td>\n",
       "      <td>120187.537332</td>\n",
       "      <td>339283.484960</td>\n",
       "      <td>76426.327729</td>\n",
       "      <td>-28950.0</td>\n",
       "      <td>0.023570</td>\n",
       "      <td>0.000007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1-Pentene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1542.189146</td>\n",
       "      <td>2215.479533</td>\n",
       "      <td>303.15</td>\n",
       "      <td>108.15</td>\n",
       "      <td>108.15</td>\n",
       "      <td>464.8</td>\n",
       "      <td>3560000.0</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>235.029826</td>\n",
       "      <td>84980.631649</td>\n",
       "      <td>361893.854967</td>\n",
       "      <td>84696.340804</td>\n",
       "      <td>-20920.0</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2-Pentene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1408.641678</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>310.05</td>\n",
       "      <td>127.55</td>\n",
       "      <td>121.80</td>\n",
       "      <td>475.0</td>\n",
       "      <td>3690000.0</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>232.999668</td>\n",
       "      <td>65970.039962</td>\n",
       "      <td>369640.183678</td>\n",
       "      <td>101378.953387</td>\n",
       "      <td>-28070.0</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000216</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name     MF        MW          CPG          CPL      TB  \\\n",
       "0     1,3-Cyclopentadiene   C5H6  66.10114  1140.819957  1802.292349  314.15   \n",
       "1            Cyclopentene   C5H8  68.11702  1194.705857  1960.689484  317.35   \n",
       "2  2-Methyl-1,3-butadiene   C5H8  68.11702  1508.531750  1960.689484  307.15   \n",
       "3          1,4-Pentadiene   C5H8  68.11702  1443.650821  1960.689484  299.05   \n",
       "4               1-Pentyne   C5H8  68.11702  1507.232005  1960.689484  313.05   \n",
       "5            Cyclopentane  C5H10  70.13290  1183.596267  2085.071702  322.35   \n",
       "6       2-Methyl-2-butene  C5H10  70.13290  1497.059793  2085.071702  311.65   \n",
       "7       3-Methyl-1-butene  C5H10  70.13290  1632.299430  2085.071702  293.25   \n",
       "8               1-Pentene  C5H10  70.13290  1542.189146  2215.479533  303.15   \n",
       "9               2-Pentene  C5H10  70.13290  1408.641678  2085.071702  310.05   \n",
       "\n",
       "    TMelt      TT     TC         PC        VC        RHOC           PSAT  \\\n",
       "0  182.05  182.05  500.0  4699960.0  0.000232  284.918707   59226.323229   \n",
       "1  138.15  138.13  506.5  4800000.0  0.000245  278.028653   50440.182509   \n",
       "2  127.15  127.15  483.3  3739997.0  0.000266  256.079023   73379.808091   \n",
       "3  125.15  125.15  478.0  3789555.0  0.000276  246.800797   97975.483765   \n",
       "4  167.15  167.15  493.4  4053000.0  0.000278  245.025252   58084.265066   \n",
       "5  179.15  179.70  511.7  4510000.0  0.000259  270.783398   42319.067142   \n",
       "6  139.15  139.42  470.0  3420000.0  0.000299  234.558194   62147.076804   \n",
       "7  104.90  104.72  452.7  3530000.0  0.000305  230.019351  120187.537332   \n",
       "8  108.15  108.15  464.8  3560000.0  0.000298  235.029826   84980.631649   \n",
       "9  127.55  121.80  475.0  3690000.0  0.000301  232.999668   65970.039962   \n",
       "\n",
       "            HVAP           HFUS        HF        Vm      Visc  \n",
       "0  405076.739586            NaN  130800.0  0.000085  0.000253  \n",
       "1  408584.752841   49326.878950   32930.0  0.000089  0.000332  \n",
       "2  361991.935213   72375.450365   75750.0  0.000097  0.000251  \n",
       "3  360428.662730   89845.386660  106380.0  0.000104  0.000195  \n",
       "4  413392.656845            NaN  144350.0  0.000103  0.000353  \n",
       "5  404672.441280    8697.772372  -77240.0  0.000095  0.000415  \n",
       "6  388900.424471  108365.688571  -42550.0  0.000107  0.000206  \n",
       "7  339283.484960   76426.327729  -28950.0  0.023570  0.000007  \n",
       "8  361893.854967   84696.340804  -20920.0  0.000110  0.000213  \n",
       "9  369640.183678  101378.953387  -28070.0  0.000108  0.000216  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ft = pd.read_csv('features_dl.csv')\n",
    "ft.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### McAuliffe solubility at 298K inserted manually from IUPAC data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>SOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1,3-Cyclopentadiene</td>\n",
       "      <td>0.0103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cyclopentene</td>\n",
       "      <td>0.0535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2-Methyl-1,3-butadiene</td>\n",
       "      <td>0.0642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1,4-Pentadiene</td>\n",
       "      <td>0.0558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1-Pentyne</td>\n",
       "      <td>0.1570</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name     SOL\n",
       "0     1,3-Cyclopentadiene  0.0103\n",
       "1            Cyclopentene  0.0535\n",
       "2  2-Methyl-1,3-butadiene  0.0642\n",
       "3          1,4-Pentadiene  0.0558\n",
       "4               1-Pentyne  0.1570"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol = pd.read_csv('sol.csv')\n",
    "sol.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Join databases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MF</th>\n",
       "      <th>MW</th>\n",
       "      <th>CPG</th>\n",
       "      <th>CPL</th>\n",
       "      <th>TB</th>\n",
       "      <th>TMelt</th>\n",
       "      <th>TT</th>\n",
       "      <th>TC</th>\n",
       "      <th>PC</th>\n",
       "      <th>VC</th>\n",
       "      <th>RHOC</th>\n",
       "      <th>PSAT</th>\n",
       "      <th>HVAP</th>\n",
       "      <th>HFUS</th>\n",
       "      <th>HF</th>\n",
       "      <th>Vm</th>\n",
       "      <th>Visc</th>\n",
       "      <th>SOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1,3-Cyclopentadiene</td>\n",
       "      <td>C5H6</td>\n",
       "      <td>66.10114</td>\n",
       "      <td>1140.819957</td>\n",
       "      <td>1802.292349</td>\n",
       "      <td>314.15</td>\n",
       "      <td>182.05</td>\n",
       "      <td>182.05</td>\n",
       "      <td>500.0</td>\n",
       "      <td>4699960.0</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>284.918707</td>\n",
       "      <td>59226.323229</td>\n",
       "      <td>405076.739586</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130800.0</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.0103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cyclopentene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1194.705857</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>317.35</td>\n",
       "      <td>138.15</td>\n",
       "      <td>138.13</td>\n",
       "      <td>506.5</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>278.028653</td>\n",
       "      <td>50440.182509</td>\n",
       "      <td>408584.752841</td>\n",
       "      <td>49326.878950</td>\n",
       "      <td>32930.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.0535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2-Methyl-1,3-butadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1508.531750</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>307.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>483.3</td>\n",
       "      <td>3739997.0</td>\n",
       "      <td>0.000266</td>\n",
       "      <td>256.079023</td>\n",
       "      <td>73379.808091</td>\n",
       "      <td>361991.935213</td>\n",
       "      <td>72375.450365</td>\n",
       "      <td>75750.0</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000251</td>\n",
       "      <td>0.0642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1,4-Pentadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1443.650821</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>299.05</td>\n",
       "      <td>125.15</td>\n",
       "      <td>125.15</td>\n",
       "      <td>478.0</td>\n",
       "      <td>3789555.0</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>246.800797</td>\n",
       "      <td>97975.483765</td>\n",
       "      <td>360428.662730</td>\n",
       "      <td>89845.386660</td>\n",
       "      <td>106380.0</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.0558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1-Pentyne</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1507.232005</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>313.05</td>\n",
       "      <td>167.15</td>\n",
       "      <td>167.15</td>\n",
       "      <td>493.4</td>\n",
       "      <td>4053000.0</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>245.025252</td>\n",
       "      <td>58084.265066</td>\n",
       "      <td>413392.656845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144350.0</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000353</td>\n",
       "      <td>0.1570</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name    MF        MW          CPG          CPL      TB  \\\n",
       "0     1,3-Cyclopentadiene  C5H6  66.10114  1140.819957  1802.292349  314.15   \n",
       "1            Cyclopentene  C5H8  68.11702  1194.705857  1960.689484  317.35   \n",
       "2  2-Methyl-1,3-butadiene  C5H8  68.11702  1508.531750  1960.689484  307.15   \n",
       "3          1,4-Pentadiene  C5H8  68.11702  1443.650821  1960.689484  299.05   \n",
       "4               1-Pentyne  C5H8  68.11702  1507.232005  1960.689484  313.05   \n",
       "\n",
       "    TMelt      TT     TC         PC        VC        RHOC          PSAT  \\\n",
       "0  182.05  182.05  500.0  4699960.0  0.000232  284.918707  59226.323229   \n",
       "1  138.15  138.13  506.5  4800000.0  0.000245  278.028653  50440.182509   \n",
       "2  127.15  127.15  483.3  3739997.0  0.000266  256.079023  73379.808091   \n",
       "3  125.15  125.15  478.0  3789555.0  0.000276  246.800797  97975.483765   \n",
       "4  167.15  167.15  493.4  4053000.0  0.000278  245.025252  58084.265066   \n",
       "\n",
       "            HVAP          HFUS        HF        Vm      Visc     SOL  \n",
       "0  405076.739586           NaN  130800.0  0.000085  0.000253  0.0103  \n",
       "1  408584.752841  49326.878950   32930.0  0.000089  0.000332  0.0535  \n",
       "2  361991.935213  72375.450365   75750.0  0.000097  0.000251  0.0642  \n",
       "3  360428.662730  89845.386660  106380.0  0.000104  0.000195  0.0558  \n",
       "4  413392.656845           NaN  144350.0  0.000103  0.000353  0.1570  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([ft.set_index('Name'),sol.set_index('Name')], axis=1, join='inner').reset_index()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imputation of missing values\n",
    "\n",
    "### We will be using iterative SVD for imputation. This is shown to work well for matrix computation (show some proof in ppt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[IterativeSVD] Iter 1: observed MAE=16436.427256\n",
      "[IterativeSVD] Iter 2: observed MAE=10700.613090\n",
      "[IterativeSVD] Iter 3: observed MAE=1040.697022\n",
      "[IterativeSVD] Iter 4: observed MAE=12.631030\n"
     ]
    }
   ],
   "source": [
    "df_numeric = df.select_dtypes(include=[np.float]).as_matrix()\n",
    "df_filled = pd.DataFrame(IterativeSVD().complete(df_numeric))\n",
    "names = ['MW','CPG','CPL','TB','TMelt','TT','TC','PC','VC','RHOC','PSAT','HVAP','HFUS', 'HF', 'Vm', 'Visc']\n",
    "\n",
    "for i in range(len(names)):    df[names[i]]=df_filled[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MF</th>\n",
       "      <th>MW</th>\n",
       "      <th>CPG</th>\n",
       "      <th>CPL</th>\n",
       "      <th>TB</th>\n",
       "      <th>TMelt</th>\n",
       "      <th>TT</th>\n",
       "      <th>TC</th>\n",
       "      <th>PC</th>\n",
       "      <th>VC</th>\n",
       "      <th>RHOC</th>\n",
       "      <th>PSAT</th>\n",
       "      <th>HVAP</th>\n",
       "      <th>HFUS</th>\n",
       "      <th>HF</th>\n",
       "      <th>Vm</th>\n",
       "      <th>Visc</th>\n",
       "      <th>SOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1,3-Cyclopentadiene</td>\n",
       "      <td>C5H6</td>\n",
       "      <td>66.10114</td>\n",
       "      <td>1140.819957</td>\n",
       "      <td>1802.292349</td>\n",
       "      <td>314.15</td>\n",
       "      <td>182.05</td>\n",
       "      <td>182.05</td>\n",
       "      <td>500.0</td>\n",
       "      <td>4699960.0</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>284.918707</td>\n",
       "      <td>59226.323229</td>\n",
       "      <td>405076.739586</td>\n",
       "      <td>59596.026999</td>\n",
       "      <td>130800.0</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.0103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cyclopentene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1194.705857</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>317.35</td>\n",
       "      <td>138.15</td>\n",
       "      <td>138.13</td>\n",
       "      <td>506.5</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>278.028653</td>\n",
       "      <td>50440.182509</td>\n",
       "      <td>408584.752841</td>\n",
       "      <td>49326.878950</td>\n",
       "      <td>32930.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.0535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2-Methyl-1,3-butadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1508.531750</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>307.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>483.3</td>\n",
       "      <td>3739997.0</td>\n",
       "      <td>0.000266</td>\n",
       "      <td>256.079023</td>\n",
       "      <td>73379.808091</td>\n",
       "      <td>361991.935213</td>\n",
       "      <td>72375.450365</td>\n",
       "      <td>75750.0</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000251</td>\n",
       "      <td>0.0642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1,4-Pentadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1443.650821</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>299.05</td>\n",
       "      <td>125.15</td>\n",
       "      <td>125.15</td>\n",
       "      <td>478.0</td>\n",
       "      <td>3789555.0</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>246.800797</td>\n",
       "      <td>97975.483765</td>\n",
       "      <td>360428.662730</td>\n",
       "      <td>89845.386660</td>\n",
       "      <td>106380.0</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.0558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1-Pentyne</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1507.232005</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>313.05</td>\n",
       "      <td>167.15</td>\n",
       "      <td>167.15</td>\n",
       "      <td>493.4</td>\n",
       "      <td>4053000.0</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>245.025252</td>\n",
       "      <td>58084.265066</td>\n",
       "      <td>413392.656845</td>\n",
       "      <td>55025.113638</td>\n",
       "      <td>144350.0</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000353</td>\n",
       "      <td>0.1570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cyclopentane</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1183.596267</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>322.35</td>\n",
       "      <td>179.15</td>\n",
       "      <td>179.70</td>\n",
       "      <td>511.7</td>\n",
       "      <td>4510000.0</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>270.783398</td>\n",
       "      <td>42319.067142</td>\n",
       "      <td>404672.441280</td>\n",
       "      <td>8697.772372</td>\n",
       "      <td>-77240.0</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000415</td>\n",
       "      <td>0.0156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2-Methyl-2-butene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1497.059793</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>311.65</td>\n",
       "      <td>139.15</td>\n",
       "      <td>139.42</td>\n",
       "      <td>470.0</td>\n",
       "      <td>3420000.0</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>234.558194</td>\n",
       "      <td>62147.076804</td>\n",
       "      <td>388900.424471</td>\n",
       "      <td>108365.688571</td>\n",
       "      <td>-42550.0</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>0.000206</td>\n",
       "      <td>0.0435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3-Methyl-1-butene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1632.299430</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>293.25</td>\n",
       "      <td>104.90</td>\n",
       "      <td>104.72</td>\n",
       "      <td>452.7</td>\n",
       "      <td>3530000.0</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>230.019351</td>\n",
       "      <td>120187.537332</td>\n",
       "      <td>339283.484960</td>\n",
       "      <td>76426.327729</td>\n",
       "      <td>-28950.0</td>\n",
       "      <td>0.023570</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.0130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1-Pentene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1542.189146</td>\n",
       "      <td>2215.479533</td>\n",
       "      <td>303.15</td>\n",
       "      <td>108.15</td>\n",
       "      <td>108.15</td>\n",
       "      <td>464.8</td>\n",
       "      <td>3560000.0</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>235.029826</td>\n",
       "      <td>84980.631649</td>\n",
       "      <td>361893.854967</td>\n",
       "      <td>84696.340804</td>\n",
       "      <td>-20920.0</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>0.0148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2-Pentene</td>\n",
       "      <td>C5H10</td>\n",
       "      <td>70.13290</td>\n",
       "      <td>1408.641678</td>\n",
       "      <td>2085.071702</td>\n",
       "      <td>310.05</td>\n",
       "      <td>127.55</td>\n",
       "      <td>121.80</td>\n",
       "      <td>475.0</td>\n",
       "      <td>3690000.0</td>\n",
       "      <td>0.000301</td>\n",
       "      <td>232.999668</td>\n",
       "      <td>65970.039962</td>\n",
       "      <td>369640.183678</td>\n",
       "      <td>101378.953387</td>\n",
       "      <td>-28070.0</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000216</td>\n",
       "      <td>0.0203</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name     MF        MW          CPG          CPL      TB  \\\n",
       "0     1,3-Cyclopentadiene   C5H6  66.10114  1140.819957  1802.292349  314.15   \n",
       "1            Cyclopentene   C5H8  68.11702  1194.705857  1960.689484  317.35   \n",
       "2  2-Methyl-1,3-butadiene   C5H8  68.11702  1508.531750  1960.689484  307.15   \n",
       "3          1,4-Pentadiene   C5H8  68.11702  1443.650821  1960.689484  299.05   \n",
       "4               1-Pentyne   C5H8  68.11702  1507.232005  1960.689484  313.05   \n",
       "5            Cyclopentane  C5H10  70.13290  1183.596267  2085.071702  322.35   \n",
       "6       2-Methyl-2-butene  C5H10  70.13290  1497.059793  2085.071702  311.65   \n",
       "7       3-Methyl-1-butene  C5H10  70.13290  1632.299430  2085.071702  293.25   \n",
       "8               1-Pentene  C5H10  70.13290  1542.189146  2215.479533  303.15   \n",
       "9               2-Pentene  C5H10  70.13290  1408.641678  2085.071702  310.05   \n",
       "\n",
       "    TMelt      TT     TC         PC        VC        RHOC           PSAT  \\\n",
       "0  182.05  182.05  500.0  4699960.0  0.000232  284.918707   59226.323229   \n",
       "1  138.15  138.13  506.5  4800000.0  0.000245  278.028653   50440.182509   \n",
       "2  127.15  127.15  483.3  3739997.0  0.000266  256.079023   73379.808091   \n",
       "3  125.15  125.15  478.0  3789555.0  0.000276  246.800797   97975.483765   \n",
       "4  167.15  167.15  493.4  4053000.0  0.000278  245.025252   58084.265066   \n",
       "5  179.15  179.70  511.7  4510000.0  0.000259  270.783398   42319.067142   \n",
       "6  139.15  139.42  470.0  3420000.0  0.000299  234.558194   62147.076804   \n",
       "7  104.90  104.72  452.7  3530000.0  0.000305  230.019351  120187.537332   \n",
       "8  108.15  108.15  464.8  3560000.0  0.000298  235.029826   84980.631649   \n",
       "9  127.55  121.80  475.0  3690000.0  0.000301  232.999668   65970.039962   \n",
       "\n",
       "            HVAP           HFUS        HF        Vm      Visc     SOL  \n",
       "0  405076.739586   59596.026999  130800.0  0.000085  0.000253  0.0103  \n",
       "1  408584.752841   49326.878950   32930.0  0.000089  0.000332  0.0535  \n",
       "2  361991.935213   72375.450365   75750.0  0.000097  0.000251  0.0642  \n",
       "3  360428.662730   89845.386660  106380.0  0.000104  0.000195  0.0558  \n",
       "4  413392.656845   55025.113638  144350.0  0.000103  0.000353  0.1570  \n",
       "5  404672.441280    8697.772372  -77240.0  0.000095  0.000415  0.0156  \n",
       "6  388900.424471  108365.688571  -42550.0  0.000107  0.000206  0.0435  \n",
       "7  339283.484960   76426.327729  -28950.0  0.023570  0.000007  0.0130  \n",
       "8  361893.854967   84696.340804  -20920.0  0.000110  0.000213  0.0148  \n",
       "9  369640.183678  101378.953387  -28070.0  0.000108  0.000216  0.0203  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.SOL >= 0]\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Baseline Performance: Linear Regression :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>SOL</td>       <th>  R-squared:         </th> <td>   0.320</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.241</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   4.051</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Thu, 02 Nov 2017</td> <th>  Prob (F-statistic):</th> <td>2.71e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>06:47:31</td>     <th>  Log-Likelihood:    </th> <td>  402.49</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>   155</td>      <th>  AIC:               </th> <td>  -771.0</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   138</td>      <th>  BIC:               </th> <td>  -719.2</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    16</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    0.1132</td> <td>    0.032</td> <td>    3.588</td> <td> 0.000</td> <td>    0.051</td> <td>    0.176</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MW</th>        <td>   -0.0003</td> <td> 7.99e-05</td> <td>   -3.849</td> <td> 0.000</td> <td>   -0.000</td> <td>   -0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CPG</th>       <td>-2.041e-05</td> <td>  1.6e-05</td> <td>   -1.280</td> <td> 0.203</td> <td> -5.2e-05</td> <td> 1.11e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CPL</th>       <td>-6.709e-06</td> <td> 1.01e-05</td> <td>   -0.667</td> <td> 0.506</td> <td>-2.66e-05</td> <td> 1.32e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TB</th>        <td> 1.856e-05</td> <td>  2.9e-05</td> <td>    0.640</td> <td> 0.523</td> <td>-3.87e-05</td> <td> 7.59e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TMelt</th>     <td>    0.0002</td> <td>    0.000</td> <td>    0.417</td> <td> 0.677</td> <td>   -0.001</td> <td>    0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TT</th>        <td>   -0.0002</td> <td>    0.000</td> <td>   -0.456</td> <td> 0.649</td> <td>   -0.001</td> <td>    0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TC</th>        <td> 1.415e-05</td> <td> 2.18e-05</td> <td>    0.650</td> <td> 0.517</td> <td>-2.89e-05</td> <td> 5.72e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PC</th>        <td> 3.026e-09</td> <td> 4.91e-09</td> <td>    0.616</td> <td> 0.539</td> <td>-6.69e-09</td> <td> 1.27e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>VC</th>        <td>   52.3788</td> <td>   17.509</td> <td>    2.992</td> <td> 0.003</td> <td>   17.759</td> <td>   86.999</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>RHOC</th>      <td>   -0.0002</td> <td> 8.37e-05</td> <td>   -2.416</td> <td> 0.017</td> <td>   -0.000</td> <td>-3.67e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PSAT</th>      <td> 2.243e-07</td> <td> 1.09e-07</td> <td>    2.055</td> <td> 0.042</td> <td> 8.51e-09</td> <td>  4.4e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HVAP</th>      <td>-4.089e-08</td> <td> 3.12e-08</td> <td>   -1.309</td> <td> 0.193</td> <td>-1.03e-07</td> <td> 2.09e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HFUS</th>      <td>  5.16e-10</td> <td>  4.8e-08</td> <td>    0.011</td> <td> 0.991</td> <td>-9.43e-08</td> <td> 9.54e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HF</th>        <td>  3.47e-08</td> <td> 1.71e-08</td> <td>    2.023</td> <td> 0.045</td> <td> 7.92e-10</td> <td> 6.86e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Vm</th>        <td>   -1.5877</td> <td>    0.812</td> <td>   -1.955</td> <td> 0.053</td> <td>   -3.194</td> <td>    0.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Visc</th>      <td>   -2.5083</td> <td>    3.933</td> <td>   -0.638</td> <td> 0.525</td> <td>  -10.286</td> <td>    5.269</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>151.448</td> <th>  Durbin-Watson:     </th> <td>   1.908</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>2834.611</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 3.560</td>  <th>  Prob(JB):          </th> <td>    0.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td>22.703</td>  <th>  Cond. No.          </th> <td>3.26e+10</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                    SOL   R-squared:                       0.320\n",
       "Model:                            OLS   Adj. R-squared:                  0.241\n",
       "Method:                 Least Squares   F-statistic:                     4.051\n",
       "Date:                Thu, 02 Nov 2017   Prob (F-statistic):           2.71e-06\n",
       "Time:                        06:47:31   Log-Likelihood:                 402.49\n",
       "No. Observations:                 155   AIC:                            -771.0\n",
       "Df Residuals:                     138   BIC:                            -719.2\n",
       "Df Model:                          16                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      0.1132      0.032      3.588      0.000       0.051       0.176\n",
       "MW            -0.0003   7.99e-05     -3.849      0.000      -0.000      -0.000\n",
       "CPG        -2.041e-05    1.6e-05     -1.280      0.203    -5.2e-05    1.11e-05\n",
       "CPL        -6.709e-06   1.01e-05     -0.667      0.506   -2.66e-05    1.32e-05\n",
       "TB          1.856e-05    2.9e-05      0.640      0.523   -3.87e-05    7.59e-05\n",
       "TMelt          0.0002      0.000      0.417      0.677      -0.001       0.001\n",
       "TT            -0.0002      0.000     -0.456      0.649      -0.001       0.001\n",
       "TC          1.415e-05   2.18e-05      0.650      0.517   -2.89e-05    5.72e-05\n",
       "PC          3.026e-09   4.91e-09      0.616      0.539   -6.69e-09    1.27e-08\n",
       "VC            52.3788     17.509      2.992      0.003      17.759      86.999\n",
       "RHOC          -0.0002   8.37e-05     -2.416      0.017      -0.000   -3.67e-05\n",
       "PSAT        2.243e-07   1.09e-07      2.055      0.042    8.51e-09     4.4e-07\n",
       "HVAP       -4.089e-08   3.12e-08     -1.309      0.193   -1.03e-07    2.09e-08\n",
       "HFUS         5.16e-10    4.8e-08      0.011      0.991   -9.43e-08    9.54e-08\n",
       "HF           3.47e-08   1.71e-08      2.023      0.045    7.92e-10    6.86e-08\n",
       "Vm            -1.5877      0.812     -1.955      0.053      -3.194       0.018\n",
       "Visc          -2.5083      3.933     -0.638      0.525     -10.286       5.269\n",
       "==============================================================================\n",
       "Omnibus:                      151.448   Durbin-Watson:                   1.908\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             2834.611\n",
       "Skew:                           3.560   Prob(JB):                         0.00\n",
       "Kurtosis:                      22.703   Cond. No.                     3.26e+10\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 3.26e+10. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = sm.ols(formula=\"SOL ~ MW + CPG + CPL + TB + TMelt + TT + TC + PC + VC + RHOC + PSAT + HVAP + HFUS + HF + Vm + Visc\", data=df).fit()\n",
    "result.summary()\n",
    "#print(result.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rr6/Hn//8ZwDAVVddhblz52Zy14mIiIiIiIgoSxSf6eHz+bBu3Trce++9ePzxx/HOO+/g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PKr5Hr9cjOTkZtbW16Natm/SeAwcO4JFHHnH53Nq1a6HT6XDdddfh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sOvPoiudkl/LuyU3VskyfPqz6Wt77U+Me7rst79oO8ly1tCa2t8OnMXnnjA5yc8YhQa8QmPmh4A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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c25d266d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,25))\n",
    "fig = sma.graphics.plot_partregress_grid(result, fig=fig)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Looks like the linear regression model is not very effective. Let us try to build a ANN. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MF</th>\n",
       "      <th>MW</th>\n",
       "      <th>CPG</th>\n",
       "      <th>CPL</th>\n",
       "      <th>TB</th>\n",
       "      <th>TMelt</th>\n",
       "      <th>TT</th>\n",
       "      <th>TC</th>\n",
       "      <th>PC</th>\n",
       "      <th>VC</th>\n",
       "      <th>RHOC</th>\n",
       "      <th>PSAT</th>\n",
       "      <th>HVAP</th>\n",
       "      <th>HFUS</th>\n",
       "      <th>HF</th>\n",
       "      <th>Vm</th>\n",
       "      <th>Visc</th>\n",
       "      <th>SOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1,3-Cyclopentadiene</td>\n",
       "      <td>C5H6</td>\n",
       "      <td>66.10114</td>\n",
       "      <td>1140.819957</td>\n",
       "      <td>1802.292349</td>\n",
       "      <td>314.15</td>\n",
       "      <td>182.05</td>\n",
       "      <td>182.05</td>\n",
       "      <td>500.0</td>\n",
       "      <td>4699960.0</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>284.918707</td>\n",
       "      <td>59226.323229</td>\n",
       "      <td>405076.739586</td>\n",
       "      <td>59596.026999</td>\n",
       "      <td>130800.0</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.0103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cyclopentene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1194.705857</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>317.35</td>\n",
       "      <td>138.15</td>\n",
       "      <td>138.13</td>\n",
       "      <td>506.5</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>278.028653</td>\n",
       "      <td>50440.182509</td>\n",
       "      <td>408584.752841</td>\n",
       "      <td>49326.878950</td>\n",
       "      <td>32930.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.0535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2-Methyl-1,3-butadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1508.531750</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>307.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>127.15</td>\n",
       "      <td>483.3</td>\n",
       "      <td>3739997.0</td>\n",
       "      <td>0.000266</td>\n",
       "      <td>256.079023</td>\n",
       "      <td>73379.808091</td>\n",
       "      <td>361991.935213</td>\n",
       "      <td>72375.450365</td>\n",
       "      <td>75750.0</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000251</td>\n",
       "      <td>0.0642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1,4-Pentadiene</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1443.650821</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>299.05</td>\n",
       "      <td>125.15</td>\n",
       "      <td>125.15</td>\n",
       "      <td>478.0</td>\n",
       "      <td>3789555.0</td>\n",
       "      <td>0.000276</td>\n",
       "      <td>246.800797</td>\n",
       "      <td>97975.483765</td>\n",
       "      <td>360428.662730</td>\n",
       "      <td>89845.386660</td>\n",
       "      <td>106380.0</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.0558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1-Pentyne</td>\n",
       "      <td>C5H8</td>\n",
       "      <td>68.11702</td>\n",
       "      <td>1507.232005</td>\n",
       "      <td>1960.689484</td>\n",
       "      <td>313.05</td>\n",
       "      <td>167.15</td>\n",
       "      <td>167.15</td>\n",
       "      <td>493.4</td>\n",
       "      <td>4053000.0</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>245.025252</td>\n",
       "      <td>58084.265066</td>\n",
       "      <td>413392.656845</td>\n",
       "      <td>55025.113638</td>\n",
       "      <td>144350.0</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000353</td>\n",
       "      <td>0.1570</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Name    MF        MW          CPG          CPL      TB  \\\n",
       "0     1,3-Cyclopentadiene  C5H6  66.10114  1140.819957  1802.292349  314.15   \n",
       "1            Cyclopentene  C5H8  68.11702  1194.705857  1960.689484  317.35   \n",
       "2  2-Methyl-1,3-butadiene  C5H8  68.11702  1508.531750  1960.689484  307.15   \n",
       "3          1,4-Pentadiene  C5H8  68.11702  1443.650821  1960.689484  299.05   \n",
       "4               1-Pentyne  C5H8  68.11702  1507.232005  1960.689484  313.05   \n",
       "\n",
       "    TMelt      TT     TC         PC        VC        RHOC          PSAT  \\\n",
       "0  182.05  182.05  500.0  4699960.0  0.000232  284.918707  59226.323229   \n",
       "1  138.15  138.13  506.5  4800000.0  0.000245  278.028653  50440.182509   \n",
       "2  127.15  127.15  483.3  3739997.0  0.000266  256.079023  73379.808091   \n",
       "3  125.15  125.15  478.0  3789555.0  0.000276  246.800797  97975.483765   \n",
       "4  167.15  167.15  493.4  4053000.0  0.000278  245.025252  58084.265066   \n",
       "\n",
       "            HVAP          HFUS        HF        Vm      Visc     SOL  \n",
       "0  405076.739586  59596.026999  130800.0  0.000085  0.000253  0.0103  \n",
       "1  408584.752841  49326.878950   32930.0  0.000089  0.000332  0.0535  \n",
       "2  361991.935213  72375.450365   75750.0  0.000097  0.000251  0.0642  \n",
       "3  360428.662730  89845.386660  106380.0  0.000104  0.000195  0.0558  \n",
       "4  413392.656845  55025.113638  144350.0  0.000103  0.000353  0.1570  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#X and Y vectors\n",
    "\n",
    "#Taking only numerical columns\n",
    "\n",
    "X = df.iloc[:, 2:18].values\n",
    "y = df.iloc[:, 18].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Splitting the dataset into the Training set and Test set\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import RobustScaler, StandardScaler\n",
    "sc = StandardScaler()\n",
    "rb = RobustScaler()\n",
    "\n",
    "\n",
    "\n",
    "#X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2)\n",
    "# X_train = sc.fit_transform(X_train)\n",
    "# X_test = sc.transform(X_test)\n",
    "X = sc.fit_transform(X)\n",
    "y=pd.cut(y, 500, labels=False)\n",
    "\n",
    "#Dataset is skewed, need to fix class weight.\n",
    "from sklearn.utils import class_weight\n",
    "class_weight = class_weight.compute_class_weight('balanced', np.unique(y), y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Importing the Keras libraries and packages\n",
    "import keras\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout\n",
    "from keras.optimizers import SGD\n",
    "from keras.callbacks import EarlyStopping\n",
    "from keras.wrappers.scikit_learn import KerasRegressor, KerasClassifier\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# define base model\n",
    "def baseline_model():\n",
    "    # create model\n",
    "    model = Sequential()\n",
    "    model.add(Dense(10, input_dim=16, kernel_initializer='normal', activation='tanh'))\n",
    "    #model.add(Dropout(0.2))\n",
    "    model.add(Dense(5, kernel_initializer='uniform', activation='relu'))\n",
    "    model.add(Dense(1, kernel_initializer='normal', activation='relu'))\n",
    "    # Compile model\n",
    "    model.compile(loss='mean_squared_error', optimizer='RMSProp' , metrics=['accuracy'])\n",
    "    #model.compile(loss='mean_squared_error', optimizer='RMSProp')\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 139 samples, validate on 16 samples\n",
      "Epoch 1/1500\n",
      "139/139 [==============================] - 1s - loss: 5784.3739 - acc: 0.3094 - val_loss: 6.4672e-04 - val_acc: 1.0000\n",
      "Epoch 2/1500\n",
      "139/139 [==============================] - 0s - loss: 5781.1786 - acc: 0.3094 - val_loss: 0.0024 - val_acc: 1.0000\n",
      "Epoch 3/1500\n",
      "139/139 [==============================] - 0s - loss: 5777.3053 - acc: 0.3094 - val_loss: 0.0052 - val_acc: 1.0000\n",
      "Epoch 4/1500\n",
      "139/139 [==============================] - 0s - loss: 5772.2379 - acc: 0.3094 - val_loss: 0.0097 - val_acc: 1.0000\n",
      "Epoch 5/1500\n",
      "139/139 [==============================] - 0s - loss: 5765.4738 - acc: 0.3094 - val_loss: 0.0166 - val_acc: 1.0000\n",
      "Epoch 6/1500\n",
      "139/139 [==============================] - 0s - loss: 5757.2794 - acc: 0.3165 - val_loss: 0.0280 - val_acc: 1.0000\n",
      "Epoch 7/1500\n",
      "139/139 [==============================] - 0s - loss: 5748.0987 - acc: 0.2806 - val_loss: 0.0462 - val_acc: 0.9375\n",
      "Epoch 8/1500\n",
      "139/139 [==============================] - 0s - loss: 5737.6160 - acc: 0.2662 - val_loss: 0.0709 - val_acc: 0.9375\n",
      "Epoch 9/1500\n",
      "139/139 [==============================] - 0s - loss: 5724.7671 - acc: 0.2446 - val_loss: 0.1073 - val_acc: 0.9375\n",
      "Epoch 10/1500\n",
      "139/139 [==============================] - 0s - loss: 5709.9965 - acc: 0.2446 - val_loss: 0.1637 - val_acc: 0.9375\n",
      "Epoch 11/1500\n",
      "139/139 [==============================] - 0s - loss: 5693.1387 - acc: 0.1942 - val_loss: 0.2418 - val_acc: 0.9375\n",
      "Epoch 12/1500\n",
      "139/139 [==============================] - 0s - loss: 5676.4351 - acc: 0.1942 - val_loss: 0.3342 - val_acc: 0.9375\n",
      "Epoch 13/1500\n",
      "139/139 [==============================] - 0s - loss: 5657.4916 - acc: 0.1942 - val_loss: 0.4563 - val_acc: 0.9375\n",
      "Epoch 14/1500\n",
      "139/139 [==============================] - 0s - loss: 5637.2462 - acc: 0.2086 - val_loss: 0.6137 - val_acc: 0.9375\n",
      "Epoch 15/1500\n",
      "139/139 [==============================] - 0s - loss: 5616.5280 - acc: 0.2086 - val_loss: 0.7810 - val_acc: 0.9375\n",
      "Epoch 16/1500\n",
      "139/139 [==============================] - 0s - loss: 5593.1396 - acc: 0.2086 - val_loss: 1.0033 - val_acc: 0.9375\n",
      "Epoch 17/1500\n",
      "139/139 [==============================] - 0s - loss: 5571.3901 - acc: 0.1942 - val_loss: 1.2231 - val_acc: 0.9375\n",
      "Epoch 18/1500\n",
      "139/139 [==============================] - 0s - loss: 5550.0066 - acc: 0.1871 - val_loss: 1.4831 - val_acc: 0.9375\n",
      "Epoch 19/1500\n",
      "139/139 [==============================] - 0s - loss: 5521.0610 - acc: 0.2086 - val_loss: 1.8475 - val_acc: 0.9375\n",
      "Epoch 20/1500\n",
      "139/139 [==============================] - 0s - loss: 5496.5170 - acc: 0.2014 - val_loss: 2.1756 - val_acc: 0.9375\n",
      "Epoch 21/1500\n",
      "139/139 [==============================] - 0s - loss: 5469.6594 - acc: 0.1871 - val_loss: 2.5876 - val_acc: 0.9375\n",
      "Epoch 22/1500\n",
      "139/139 [==============================] - 0s - loss: 5444.0401 - acc: 0.1871 - val_loss: 3.0405 - val_acc: 0.9375\n",
      "Epoch 23/1500\n",
      "139/139 [==============================] - 0s - loss: 5415.0437 - acc: 0.1942 - val_loss: 3.5137 - val_acc: 0.9375\n",
      "Epoch 24/1500\n",
      "139/139 [==============================] - 0s - loss: 5390.7204 - acc: 0.1871 - val_loss: 3.9967 - val_acc: 0.9375\n",
      "Epoch 25/1500\n",
      "139/139 [==============================] - 0s - loss: 5361.5439 - acc: 0.1871 - val_loss: 4.6621 - val_acc: 0.9375\n",
      "Epoch 26/1500\n",
      "139/139 [==============================] - 0s - loss: 5331.7689 - acc: 0.1799 - val_loss: 5.3553 - val_acc: 0.9375\n",
      "Epoch 27/1500\n",
      "139/139 [==============================] - 0s - loss: 5301.5805 - acc: 0.0576 - val_loss: 6.0622 - val_acc: 0.0000e+00\n",
      "Epoch 28/1500\n",
      "139/139 [==============================] - 0s - loss: 5270.6102 - acc: 0.0288 - val_loss: 6.8709 - val_acc: 0.0000e+00\n",
      "Epoch 29/1500\n",
      "139/139 [==============================] - 0s - loss: 5238.2852 - acc: 0.0288 - val_loss: 7.7771 - val_acc: 0.0000e+00\n",
      "Epoch 30/1500\n",
      "139/139 [==============================] - 0s - loss: 5208.1731 - acc: 0.0288 - val_loss: 8.7143 - val_acc: 0.0000e+00\n",
      "Epoch 31/1500\n",
      "139/139 [==============================] - 0s - loss: 5181.0155 - acc: 0.0360 - val_loss: 9.5316 - val_acc: 0.0000e+00\n",
      "Epoch 32/1500\n",
      "139/139 [==============================] - 0s - loss: 5154.3758 - acc: 0.0216 - val_loss: 10.6063 - val_acc: 0.0000e+00\n",
      "Epoch 33/1500\n",
      "139/139 [==============================] - 0s - loss: 5119.7873 - acc: 0.0288 - val_loss: 11.8191 - val_acc: 0.0000e+00\n",
      "Epoch 34/1500\n",
      "139/139 [==============================] - 0s - loss: 5094.4450 - acc: 0.0360 - val_loss: 12.8155 - val_acc: 0.0000e+00\n",
      "Epoch 35/1500\n",
      "139/139 [==============================] - 0s - loss: 5063.9172 - acc: 0.0216 - val_loss: 14.1909 - val_acc: 0.0000e+00\n",
      "Epoch 36/1500\n",
      "139/139 [==============================] - 0s - loss: 5039.2070 - acc: 0.0647 - val_loss: 15.2737 - val_acc: 0.0000e+00\n",
      "Epoch 37/1500\n",
      "139/139 [==============================] - 0s - loss: 5007.9122 - acc: 0.0432 - val_loss: 16.9647 - val_acc: 0.0000e+00\n",
      "Epoch 38/1500\n",
      "139/139 [==============================] - 0s - loss: 4978.6456 - acc: 0.0288 - val_loss: 18.3559 - val_acc: 0.0000e+00\n",
      "Epoch 39/1500\n",
      "139/139 [==============================] - 0s - loss: 4949.7620 - acc: 0.0216 - val_loss: 19.9979 - val_acc: 0.0000e+00\n",
      "Epoch 40/1500\n",
      "139/139 [==============================] - 0s - loss: 4921.3858 - acc: 0.0216 - val_loss: 21.5921 - val_acc: 0.0000e+00\n",
      "Epoch 41/1500\n",
      "139/139 [==============================] - 0s - loss: 4897.9356 - acc: 0.0216 - val_loss: 23.1959 - val_acc: 0.0000e+00\n",
      "Epoch 42/1500\n",
      "139/139 [==============================] - 0s - loss: 4874.3275 - acc: 0.0432 - val_loss: 24.7870 - val_acc: 0.0000e+00\n",
      "Epoch 43/1500\n",
      "139/139 [==============================] - 0s - loss: 4848.5360 - acc: 0.0360 - val_loss: 26.6539 - val_acc: 0.0000e+00\n",
      "Epoch 44/1500\n",
      "139/139 [==============================] - 0s - loss: 4827.5047 - acc: 0.0288 - val_loss: 28.1662 - val_acc: 0.0000e+00\n",
      "Epoch 45/1500\n",
      "139/139 [==============================] - 0s - loss: 4804.0340 - acc: 0.0288 - val_loss: 30.3703 - val_acc: 0.0000e+00\n",
      "Epoch 46/1500\n",
      "139/139 [==============================] - 0s - loss: 4780.3352 - acc: 0.0288 - val_loss: 32.0813 - val_acc: 0.0000e+00\n",
      "Epoch 47/1500\n",
      "139/139 [==============================] - 0s - loss: 4760.6886 - acc: 0.0288 - val_loss: 34.0817 - val_acc: 0.0000e+00\n",
      "Epoch 48/1500\n",
      "139/139 [==============================] - 0s - loss: 4737.8763 - acc: 0.0360 - val_loss: 36.3159 - val_acc: 0.0000e+00\n",
      "Epoch 49/1500\n",
      "139/139 [==============================] - 0s - loss: 4716.9911 - acc: 0.0360 - val_loss: 38.4252 - val_acc: 0.0000e+00\n",
      "Epoch 50/1500\n",
      "139/139 [==============================] - 0s - loss: 4698.1821 - acc: 0.0288 - val_loss: 40.5012 - val_acc: 0.0000e+00\n",
      "Epoch 51/1500\n",
      "139/139 [==============================] - 0s - loss: 4681.1334 - acc: 0.0360 - val_loss: 42.0904 - val_acc: 0.0000e+00\n",
      "Epoch 52/1500\n",
      "139/139 [==============================] - 0s - loss: 4666.0010 - acc: 0.0432 - val_loss: 44.0771 - val_acc: 0.0000e+00\n",
      "Epoch 53/1500\n",
      "139/139 [==============================] - 0s - loss: 4650.0415 - acc: 0.0432 - val_loss: 46.1970 - val_acc: 0.0000e+00\n",
      "Epoch 54/1500\n",
      "139/139 [==============================] - 0s - loss: 4632.7379 - acc: 0.0432 - val_loss: 48.6444 - val_acc: 0.0000e+00\n",
      "Epoch 55/1500\n",
      "139/139 [==============================] - 0s - loss: 4617.3719 - acc: 0.0432 - val_loss: 50.5624 - val_acc: 0.0000e+00\n",
      "Epoch 56/1500\n",
      "139/139 [==============================] - 0s - loss: 4603.5358 - acc: 0.0216 - val_loss: 52.7056 - val_acc: 0.0000e+00\n",
      "Epoch 57/1500\n",
      "139/139 [==============================] - 0s - loss: 4590.7919 - acc: 0.0432 - val_loss: 54.9805 - val_acc: 0.0000e+00\n",
      "Epoch 58/1500\n",
      "139/139 [==============================] - 0s - loss: 4575.6968 - acc: 0.0360 - val_loss: 57.3495 - val_acc: 0.0000e+00\n",
      "Epoch 59/1500\n",
      "139/139 [==============================] - 0s - loss: 4563.8586 - acc: 0.0432 - val_loss: 59.2292 - val_acc: 0.0000e+00\n",
      "Epoch 60/1500\n",
      "139/139 [==============================] - 0s - loss: 4554.9049 - acc: 0.0504 - val_loss: 61.3211 - val_acc: 0.0000e+00\n",
      "Epoch 61/1500\n",
      "139/139 [==============================] - 0s - loss: 4540.9900 - acc: 0.0360 - val_loss: 63.3946 - val_acc: 0.0000e+00\n",
      "Epoch 62/1500\n",
      "139/139 [==============================] - 0s - loss: 4530.1704 - acc: 0.0360 - val_loss: 65.4721 - val_acc: 0.0000e+00\n",
      "Epoch 63/1500\n",
      "139/139 [==============================] - 0s - loss: 4521.7817 - acc: 0.0288 - val_loss: 67.3325 - val_acc: 0.0000e+00\n",
      "Epoch 64/1500\n",
      "139/139 [==============================] - 0s - loss: 4512.9776 - acc: 0.0360 - val_loss: 69.0140 - val_acc: 0.0000e+00\n",
      "Epoch 65/1500\n",
      "139/139 [==============================] - 0s - loss: 4503.0605 - acc: 0.0216 - val_loss: 71.0355 - val_acc: 0.0000e+00\n",
      "Epoch 66/1500\n",
      "139/139 [==============================] - 0s - loss: 4493.8304 - acc: 0.0216 - val_loss: 72.9158 - val_acc: 0.0000e+00\n",
      "Epoch 67/1500\n",
      "139/139 [==============================] - 0s - loss: 4484.7805 - acc: 0.0216 - val_loss: 74.6587 - val_acc: 0.0000e+00\n",
      "Epoch 68/1500\n",
      "139/139 [==============================] - 0s - loss: 4477.5503 - acc: 0.0216 - val_loss: 76.0739 - val_acc: 0.0000e+00\n",
      "Epoch 69/1500\n",
      "139/139 [==============================] - 0s - loss: 4467.9191 - acc: 0.0360 - val_loss: 78.1326 - val_acc: 0.0000e+00\n",
      "Epoch 70/1500\n",
      "139/139 [==============================] - 0s - loss: 4457.3387 - acc: 0.0216 - val_loss: 80.3700 - val_acc: 0.0000e+00\n",
      "Epoch 71/1500\n",
      "139/139 [==============================] - 0s - loss: 4448.1106 - acc: 0.0216 - val_loss: 82.5127 - val_acc: 0.0000e+00\n",
      "Epoch 72/1500\n",
      "139/139 [==============================] - 0s - loss: 4438.3825 - acc: 0.0216 - val_loss: 84.4127 - val_acc: 0.0000e+00\n",
      "Epoch 73/1500\n",
      "139/139 [==============================] - 0s - loss: 4428.4173 - acc: 0.0216 - val_loss: 86.3711 - val_acc: 0.0000e+00\n",
      "Epoch 74/1500\n",
      "139/139 [==============================] - 0s - loss: 4418.5171 - acc: 0.0216 - val_loss: 88.1437 - val_acc: 0.0000e+00\n",
      "Epoch 75/1500\n",
      "139/139 [==============================] - 0s - loss: 4407.5006 - acc: 0.0216 - val_loss: 89.7380 - val_acc: 0.0000e+00\n",
      "Epoch 76/1500\n",
      "139/139 [==============================] - 0s - loss: 4399.1799 - acc: 0.0216 - val_loss: 91.4647 - val_acc: 0.0000e+00\n",
      "Epoch 77/1500\n",
      "139/139 [==============================] - 0s - loss: 4388.1961 - acc: 0.0216 - val_loss: 93.4388 - val_acc: 0.0000e+00\n",
      "Epoch 78/1500\n",
      "139/139 [==============================] - 0s - loss: 4374.8547 - acc: 0.0216 - val_loss: 96.0792 - val_acc: 0.0000e+00\n",
      "Epoch 79/1500\n",
      "139/139 [==============================] - 0s - loss: 4360.2638 - acc: 0.0288 - val_loss: 98.7521 - val_acc: 0.0000e+00\n",
      "Epoch 80/1500\n",
      "139/139 [==============================] - 0s - loss: 4345.9587 - acc: 0.0288 - val_loss: 101.2050 - val_acc: 0.0000e+00\n",
      "Epoch 81/1500\n",
      "139/139 [==============================] - 0s - loss: 4331.0630 - acc: 0.0288 - val_loss: 103.8191 - val_acc: 0.0000e+00\n",
      "Epoch 82/1500\n",
      "139/139 [==============================] - 0s - loss: 4315.0210 - acc: 0.0216 - val_loss: 106.3976 - val_acc: 0.0000e+00\n",
      "Epoch 83/1500\n",
      "139/139 [==============================] - 0s - loss: 4300.4458 - acc: 0.0288 - val_loss: 109.1571 - val_acc: 0.0000e+00\n",
      "Epoch 84/1500\n",
      "139/139 [==============================] - 0s - loss: 4283.9303 - acc: 0.0288 - val_loss: 112.1301 - val_acc: 0.0000e+00\n",
      "Epoch 85/1500\n",
      "139/139 [==============================] - 0s - loss: 4266.7456 - acc: 0.0288 - val_loss: 115.2207 - val_acc: 0.0000e+00\n",
      "Epoch 86/1500\n",
      "139/139 [==============================] - 0s - loss: 4249.8920 - acc: 0.0288 - val_loss: 117.9722 - val_acc: 0.0000e+00\n",
      "Epoch 87/1500\n",
      "139/139 [==============================] - 0s - loss: 4235.5845 - acc: 0.0216 - val_loss: 119.9544 - val_acc: 0.0000e+00\n",
      "Epoch 88/1500\n",
      "139/139 [==============================] - 0s - loss: 4222.2913 - acc: 0.0216 - val_loss: 122.7710 - val_acc: 0.0000e+00\n",
      "Epoch 89/1500\n",
      "139/139 [==============================] - 0s - loss: 4207.2172 - acc: 0.0216 - val_loss: 125.1394 - val_acc: 0.0000e+00\n",
      "Epoch 90/1500\n",
      "139/139 [==============================] - 0s - loss: 4192.7813 - acc: 0.0216 - val_loss: 128.7438 - val_acc: 0.0000e+00\n",
      "Epoch 91/1500\n",
      "139/139 [==============================] - 0s - loss: 4177.2648 - acc: 0.0216 - val_loss: 131.5932 - val_acc: 0.0000e+00\n",
      "Epoch 92/1500\n",
      "139/139 [==============================] - 0s - loss: 4161.2945 - acc: 0.0216 - val_loss: 134.6557 - val_acc: 0.0000e+00\n",
      "Epoch 93/1500\n",
      "139/139 [==============================] - 0s - loss: 4145.5716 - acc: 0.0288 - val_loss: 137.6743 - val_acc: 0.0000e+00\n",
      "Epoch 94/1500\n",
      "139/139 [==============================] - 0s - loss: 4129.0900 - acc: 0.0288 - val_loss: 141.4549 - val_acc: 0.0000e+00\n",
      "Epoch 95/1500\n",
      "139/139 [==============================] - 0s - loss: 4112.3975 - acc: 0.0360 - val_loss: 145.3187 - val_acc: 0.0000e+00\n",
      "Epoch 96/1500\n",
      "139/139 [==============================] - 0s - loss: 4095.8662 - acc: 0.0288 - val_loss: 148.9546 - val_acc: 0.0000e+00\n",
      "Epoch 97/1500\n",
      "139/139 [==============================] - 0s - loss: 4079.5389 - acc: 0.0216 - val_loss: 153.2007 - val_acc: 0.0000e+00\n",
      "Epoch 98/1500\n",
      "139/139 [==============================] - 0s - loss: 4060.9491 - acc: 0.0216 - val_loss: 157.6426 - val_acc: 0.0000e+00\n",
      "Epoch 99/1500\n",
      "139/139 [==============================] - 0s - loss: 4044.2204 - acc: 0.0216 - val_loss: 161.5927 - val_acc: 0.0000e+00\n",
      "Epoch 100/1500\n",
      "139/139 [==============================] - 0s - loss: 4027.8366 - acc: 0.0144 - val_loss: 165.0716 - val_acc: 0.0000e+00\n",
      "Epoch 101/1500\n",
      "139/139 [==============================] - 0s - loss: 4012.8284 - acc: 0.0216 - val_loss: 168.8064 - val_acc: 0.0000e+00\n",
      "Epoch 102/1500\n",
      "139/139 [==============================] - 0s - loss: 3999.0596 - acc: 0.0216 - val_loss: 171.7889 - val_acc: 0.0000e+00\n",
      "Epoch 103/1500\n",
      "139/139 [==============================] - 0s - loss: 3982.4513 - acc: 0.0216 - val_loss: 176.6808 - val_acc: 0.0000e+00\n",
      "Epoch 104/1500\n",
      "139/139 [==============================] - 0s - loss: 3967.8143 - acc: 0.0288 - val_loss: 180.0730 - val_acc: 0.0000e+00\n",
      "Epoch 105/1500\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 247/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    {
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     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 624/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 750/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 876/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "139/139 [==============================] - 0s - loss: 670.9372 - acc: 0.1799 - val_loss: 0.9289 - val_acc: 0.9375\n",
      "Epoch 877/1500\n",
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      "Epoch 878/1500\n",
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      "Epoch 879/1500\n",
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      "Epoch 886/1500\n",
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      "Epoch 896/1500\n",
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      "Epoch 900/1500\n",
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      "Epoch 904/1500\n",
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      "Epoch 906/1500\n",
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      "Epoch 908/1500\n",
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      "Epoch 954/1500\n",
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      "Epoch 958/1500\n",
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      "Epoch 961/1500\n",
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      "Epoch 963/1500\n",
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      "Epoch 973/1500\n",
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      "Epoch 975/1500\n",
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      "Epoch 976/1500\n",
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      "Epoch 978/1500\n",
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      "Epoch 979/1500\n",
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      "Epoch 980/1500\n",
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      "Epoch 982/1500\n",
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      "Epoch 983/1500\n",
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      "Epoch 984/1500\n",
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      "Epoch 986/1500\n",
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      "Epoch 987/1500\n",
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      "139/139 [==============================] - 0s - loss: 473.5945 - acc: 0.1871 - val_loss: 2.2760 - val_acc: 0.8750\n",
      "Epoch 989/1500\n",
      "139/139 [==============================] - 0s - loss: 470.9300 - acc: 0.1799 - val_loss: 2.2801 - val_acc: 0.8750\n",
      "Epoch 990/1500\n",
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      "Epoch 991/1500\n",
      "139/139 [==============================] - 0s - loss: 467.8666 - acc: 0.1799 - val_loss: 2.2887 - val_acc: 0.8750\n",
      "Epoch 992/1500\n",
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      "Epoch 993/1500\n",
      "139/139 [==============================] - 0s - loss: 466.0766 - acc: 0.1871 - val_loss: 2.2980 - val_acc: 0.8750\n",
      "Epoch 994/1500\n",
      "139/139 [==============================] - 0s - loss: 465.3404 - acc: 0.2014 - val_loss: 2.3026 - val_acc: 0.8750\n",
      "Epoch 995/1500\n",
      "139/139 [==============================] - 0s - loss: 463.0913 - acc: 0.1871 - val_loss: 2.3074 - val_acc: 0.8750\n",
      "Epoch 996/1500\n",
      "139/139 [==============================] - 0s - loss: 461.4324 - acc: 0.1727 - val_loss: 2.3123 - val_acc: 0.8750\n",
      "Epoch 997/1500\n",
      "139/139 [==============================] - 0s - loss: 459.4625 - acc: 0.1871 - val_loss: 2.3175 - val_acc: 0.8750\n",
      "Epoch 998/1500\n",
      "139/139 [==============================] - 0s - loss: 454.6175 - acc: 0.1871 - val_loss: 2.3226 - val_acc: 0.8750\n",
      "Epoch 999/1500\n",
      "139/139 [==============================] - 0s - loss: 457.1036 - acc: 0.1871 - val_loss: 2.3264 - val_acc: 0.8750\n",
      "Epoch 1000/1500\n",
      "139/139 [==============================] - 0s - loss: 455.7388 - acc: 0.1942 - val_loss: 2.3318 - val_acc: 0.8750\n",
      "Epoch 1001/1500\n",
      "139/139 [==============================] - 0s - loss: 455.3358 - acc: 0.1942 - val_loss: 2.3361 - val_acc: 0.8750\n",
      "Epoch 1002/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "139/139 [==============================] - 0s - loss: 451.0673 - acc: 0.1727 - val_loss: 2.3408 - val_acc: 0.8750\n",
      "Epoch 1003/1500\n",
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      "Epoch 1004/1500\n",
      "139/139 [==============================] - 0s - loss: 448.9897 - acc: 0.1799 - val_loss: 2.3493 - val_acc: 0.8750\n",
      "Epoch 1005/1500\n",
      "139/139 [==============================] - 0s - loss: 449.2785 - acc: 0.1799 - val_loss: 2.3521 - val_acc: 0.8750\n",
      "Epoch 1006/1500\n",
      "139/139 [==============================] - 0s - loss: 447.3329 - acc: 0.1942 - val_loss: 2.3557 - val_acc: 0.8750\n",
      "Epoch 1007/1500\n",
      "139/139 [==============================] - 0s - loss: 447.0494 - acc: 0.2086 - val_loss: 2.3587 - val_acc: 0.8750\n",
      "Epoch 1008/1500\n",
      "139/139 [==============================] - 0s - loss: 442.5573 - acc: 0.2014 - val_loss: 2.3629 - val_acc: 0.8750\n",
      "Epoch 1009/1500\n",
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      "Epoch 1010/1500\n",
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      "Epoch 1011/1500\n",
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      "Epoch 1012/1500\n",
      "139/139 [==============================] - 0s - loss: 439.9899 - acc: 0.1871 - val_loss: 2.3810 - val_acc: 0.8750\n",
      "Epoch 1013/1500\n",
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      "Epoch 1014/1500\n",
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      "Epoch 1015/1500\n",
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      "Epoch 1016/1500\n",
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      "Epoch 1017/1500\n",
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      "Epoch 1018/1500\n",
      "139/139 [==============================] - 0s - loss: 430.3938 - acc: 0.1871 - val_loss: 2.4067 - val_acc: 0.8750\n",
      "Epoch 1019/1500\n",
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      "Epoch 1020/1500\n",
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      "Epoch 1021/1500\n",
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      "Epoch 1022/1500\n",
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      "Epoch 1023/1500\n",
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      "Epoch 1024/1500\n",
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      "Epoch 1025/1500\n",
      "139/139 [==============================] - 0s - loss: 423.8234 - acc: 0.1871 - val_loss: 2.4368 - val_acc: 0.8750\n",
      "Epoch 1026/1500\n",
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      "Epoch 1027/1500\n",
      "139/139 [==============================] - 0s - loss: 418.2386 - acc: 0.2014 - val_loss: 2.4448 - val_acc: 0.8750\n",
      "Epoch 1028/1500\n",
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      "Epoch 1029/1500\n",
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      "Epoch 1128/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Epoch 1129/1500\n",
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      "Epoch 1249/1500\n",
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      "Epoch 1250/1500\n",
      "139/139 [==============================] - 0s - loss: 237.7572 - acc: 0.2230 - val_loss: 3.6886 - val_acc: 0.8750\n",
      "Epoch 1251/1500\n",
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      "Epoch 1252/1500\n",
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      "Epoch 1253/1500\n",
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      "Epoch 1254/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "139/139 [==============================] - 0s - loss: 237.5596 - acc: 0.2086 - val_loss: 3.7113 - val_acc: 0.8750\n",
      "Epoch 1255/1500\n",
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      "Epoch 1257/1500\n",
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      "Epoch 1258/1500\n",
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      "Epoch 1259/1500\n",
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      "Epoch 1260/1500\n",
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      "Epoch 1261/1500\n",
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      "Epoch 1263/1500\n",
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      "Epoch 1265/1500\n",
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      "Epoch 1266/1500\n",
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      "Epoch 1267/1500\n",
      "139/139 [==============================] - 0s - loss: 232.1713 - acc: 0.2158 - val_loss: 3.7798 - val_acc: 0.8750\n",
      "Epoch 1268/1500\n",
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      "Epoch 1269/1500\n",
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      "Epoch 1270/1500\n",
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      "Epoch 1275/1500\n",
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      "Epoch 1277/1500\n",
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      "Epoch 1295/1500\n",
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      "Epoch 1370/1500\n",
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      "Epoch 1371/1500\n",
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      "Epoch 1372/1500\n",
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      "Epoch 1378/1500\n",
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      "Epoch 1380/1500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "139/139 [==============================] - 0s - loss: 215.4608 - acc: 0.2158 - val_loss: 4.5509 - val_acc: 0.8750\n",
      "Epoch 1381/1500\n",
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      "Epoch 1384/1500\n",
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      "Epoch 1385/1500\n",
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      "Epoch 1387/1500\n",
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      "Epoch 1390/1500\n",
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      "Epoch 1393/1500\n",
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      "Epoch 1394/1500\n",
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      "Epoch 1395/1500\n",
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      "Epoch 1396/1500\n",
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      "Epoch 1399/1500\n",
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      "Epoch 1400/1500\n",
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      "Epoch 1401/1500\n",
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      "Epoch 1402/1500\n",
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      "Epoch 1403/1500\n",
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      "Epoch 1404/1500\n",
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      "Epoch 1410/1500\n",
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      "Epoch 1411/1500\n",
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      "Epoch 1412/1500\n",
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      "Epoch 1413/1500\n",
      "139/139 [==============================] - ETA: 0s - loss: 144.6306 - acc: 0.2538  - 0s - loss: 215.2501 - acc: 0.2590 - val_loss: 4.7790 - val_acc: 0.8750\n",
      "Epoch 1414/1500\n",
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      "Epoch 1419/1500\n",
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      "Epoch 1420/1500\n",
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      "Epoch 1421/1500\n",
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      "Epoch 1426/1500\n",
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      "139/139 [==============================] - 0s - loss: 214.8339 - acc: 0.2374 - val_loss: 4.8840 - val_acc: 0.8750\n",
      "Epoch 1428/1500\n",
      "139/139 [==============================] - 0s - loss: 213.8303 - acc: 0.2014 - val_loss: 4.8920 - val_acc: 0.8750\n",
      "Epoch 1429/1500\n",
      "139/139 [==============================] - 0s - loss: 215.1414 - acc: 0.2230 - val_loss: 4.8989 - val_acc: 0.8750\n",
      "Epoch 1430/1500\n",
      "139/139 [==============================] - 0s - loss: 213.6412 - acc: 0.2230 - val_loss: 4.9069 - val_acc: 0.8750\n",
      "Epoch 1431/1500\n",
      "139/139 [==============================] - 0s - loss: 214.7999 - acc: 0.2230 - val_loss: 4.9133 - val_acc: 0.8750\n",
      "Epoch 1432/1500\n",
      "139/139 [==============================] - 0s - loss: 214.3993 - acc: 0.2374 - val_loss: 4.9208 - val_acc: 0.8750\n",
      "Epoch 1433/1500\n",
      "139/139 [==============================] - 0s - loss: 214.5985 - acc: 0.2230 - val_loss: 4.9296 - val_acc: 0.8750\n",
      "Epoch 1434/1500\n",
      "139/139 [==============================] - 0s - loss: 213.7175 - acc: 0.2374 - val_loss: 4.9345 - val_acc: 0.8750\n",
      "Epoch 1435/1500\n",
      "139/139 [==============================] - 0s - loss: 214.6627 - acc: 0.1942 - val_loss: 4.9439 - val_acc: 0.8750\n",
      "Epoch 1436/1500\n",
      "139/139 [==============================] - 0s - loss: 213.8454 - acc: 0.2446 - val_loss: 4.9520 - val_acc: 0.8750\n",
      "Epoch 1437/1500\n",
      "139/139 [==============================] - 0s - loss: 213.9903 - acc: 0.2446 - val_loss: 4.9595 - val_acc: 0.8750\n",
      "Epoch 1438/1500\n",
      "139/139 [==============================] - 0s - loss: 214.0491 - acc: 0.2158 - val_loss: 4.9669 - val_acc: 0.8750\n",
      "Epoch 1439/1500\n",
      "139/139 [==============================] - 0s - loss: 214.6062 - acc: 0.2302 - val_loss: 4.9732 - val_acc: 0.8750\n",
      "Epoch 1440/1500\n",
      "139/139 [==============================] - 0s - loss: 213.4446 - acc: 0.2518 - val_loss: 4.9796 - val_acc: 0.8750\n",
      "Epoch 1441/1500\n",
      "139/139 [==============================] - 0s - loss: 213.4406 - acc: 0.2014 - val_loss: 4.9817 - val_acc: 0.8750\n",
      "Epoch 1442/1500\n",
      "139/139 [==============================] - 0s - loss: 214.8666 - acc: 0.2158 - val_loss: 4.9927 - val_acc: 0.8750\n",
      "Epoch 1443/1500\n",
      "139/139 [==============================] - 0s - loss: 214.2277 - acc: 0.2518 - val_loss: 4.9999 - val_acc: 0.8750\n",
      "Epoch 1444/1500\n",
      "139/139 [==============================] - 0s - loss: 213.7772 - acc: 0.2086 - val_loss: 5.0058 - val_acc: 0.8750\n",
      "Epoch 1445/1500\n",
      "139/139 [==============================] - 0s - loss: 214.0124 - acc: 0.2446 - val_loss: 5.0123 - val_acc: 0.8750\n",
      "Epoch 1446/1500\n",
      "139/139 [==============================] - 0s - loss: 213.6074 - acc: 0.2374 - val_loss: 5.0197 - val_acc: 0.8750\n",
      "Epoch 1447/1500\n",
      "139/139 [==============================] - 0s - loss: 213.7612 - acc: 0.2374 - val_loss: 5.0256 - val_acc: 0.8750\n",
      "Epoch 1448/1500\n",
      "139/139 [==============================] - 0s - loss: 213.2536 - acc: 0.2374 - val_loss: 5.0339 - val_acc: 0.8750\n",
      "Epoch 1449/1500\n",
      "139/139 [==============================] - 0s - loss: 214.7530 - acc: 0.1942 - val_loss: 5.0438 - val_acc: 0.8750\n",
      "Epoch 1450/1500\n",
      "139/139 [==============================] - 0s - loss: 213.0260 - acc: 0.2302 - val_loss: 5.0514 - val_acc: 0.8750\n",
      "Epoch 1451/1500\n",
      "139/139 [==============================] - 0s - loss: 213.9044 - acc: 0.2374 - val_loss: 5.0572 - val_acc: 0.8750\n",
      "Epoch 1452/1500\n",
      "139/139 [==============================] - 0s - loss: 213.6556 - acc: 0.2230 - val_loss: 5.0622 - val_acc: 0.8750\n",
      "Epoch 1453/1500\n",
      "139/139 [==============================] - 0s - loss: 213.3932 - acc: 0.2374 - val_loss: 5.0706 - val_acc: 0.8750\n",
      "Epoch 1454/1500\n",
      "139/139 [==============================] - 0s - loss: 213.1877 - acc: 0.2086 - val_loss: 5.0779 - val_acc: 0.8750\n",
      "Epoch 1455/1500\n",
      "139/139 [==============================] - 0s - loss: 213.4251 - acc: 0.2158 - val_loss: 5.0864 - val_acc: 0.8750\n",
      "Epoch 1456/1500\n",
      "139/139 [==============================] - 0s - loss: 213.0428 - acc: 0.2014 - val_loss: 5.0940 - val_acc: 0.8750\n",
      "Epoch 1457/1500\n",
      "139/139 [==============================] - 0s - loss: 213.0425 - acc: 0.2446 - val_loss: 5.1009 - val_acc: 0.8750\n",
      "Epoch 1458/1500\n",
      "139/139 [==============================] - 0s - loss: 212.8209 - acc: 0.2086 - val_loss: 5.1054 - val_acc: 0.8750\n",
      "Epoch 1459/1500\n",
      "139/139 [==============================] - 0s - loss: 213.2565 - acc: 0.2158 - val_loss: 5.1116 - val_acc: 0.8750\n",
      "Epoch 1460/1500\n",
      "139/139 [==============================] - 0s - loss: 213.1303 - acc: 0.2302 - val_loss: 5.1193 - val_acc: 0.8750\n",
      "Epoch 1461/1500\n",
      "139/139 [==============================] - 0s - loss: 212.6631 - acc: 0.2230 - val_loss: 5.1263 - val_acc: 0.8750\n",
      "Epoch 1462/1500\n",
      "139/139 [==============================] - 0s - loss: 212.8223 - acc: 0.2230 - val_loss: 5.1317 - val_acc: 0.8750\n",
      "Epoch 1463/1500\n",
      "139/139 [==============================] - 0s - loss: 212.9857 - acc: 0.2086 - val_loss: 5.1381 - val_acc: 0.8750\n",
      "Epoch 1464/1500\n",
      "139/139 [==============================] - 0s - loss: 212.8305 - acc: 0.2302 - val_loss: 5.1459 - val_acc: 0.8750\n",
      "Epoch 1465/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4650 - acc: 0.2230 - val_loss: 5.1496 - val_acc: 0.8750\n",
      "Epoch 1466/1500\n",
      "139/139 [==============================] - 0s - loss: 213.1473 - acc: 0.2230 - val_loss: 5.1580 - val_acc: 0.8750\n",
      "Epoch 1467/1500\n",
      "139/139 [==============================] - 0s - loss: 212.6539 - acc: 0.2446 - val_loss: 5.1651 - val_acc: 0.8750\n",
      "Epoch 1468/1500\n",
      "139/139 [==============================] - 0s - loss: 212.7320 - acc: 0.2158 - val_loss: 5.1698 - val_acc: 0.8750\n",
      "Epoch 1469/1500\n",
      "139/139 [==============================] - 0s - loss: 212.7416 - acc: 0.2446 - val_loss: 5.1778 - val_acc: 0.8750\n",
      "Epoch 1470/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4811 - acc: 0.2230 - val_loss: 5.1842 - val_acc: 0.8750\n",
      "Epoch 1471/1500\n",
      "139/139 [==============================] - 0s - loss: 212.7869 - acc: 0.2374 - val_loss: 5.1903 - val_acc: 0.8750\n",
      "Epoch 1472/1500\n",
      "139/139 [==============================] - 0s - loss: 213.0483 - acc: 0.2230 - val_loss: 5.1991 - val_acc: 0.8750\n",
      "Epoch 1473/1500\n",
      "139/139 [==============================] - 0s - loss: 212.5959 - acc: 0.2518 - val_loss: 5.2065 - val_acc: 0.8750\n",
      "Epoch 1474/1500\n",
      "139/139 [==============================] - 0s - loss: 212.7998 - acc: 0.2086 - val_loss: 5.2126 - val_acc: 0.8750\n",
      "Epoch 1475/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4746 - acc: 0.2302 - val_loss: 5.2198 - val_acc: 0.8750\n",
      "Epoch 1476/1500\n",
      "139/139 [==============================] - 0s - loss: 211.9999 - acc: 0.2302 - val_loss: 5.2283 - val_acc: 0.8750\n",
      "Epoch 1477/1500\n",
      "139/139 [==============================] - 0s - loss: 212.3474 - acc: 0.2158 - val_loss: 5.2340 - val_acc: 0.8750\n",
      "Epoch 1478/1500\n",
      "139/139 [==============================] - 0s - loss: 211.5074 - acc: 0.2158 - val_loss: 5.2416 - val_acc: 0.8750\n",
      "Epoch 1479/1500\n",
      "139/139 [==============================] - 0s - loss: 212.7685 - acc: 0.2518 - val_loss: 5.2455 - val_acc: 0.8750\n",
      "Epoch 1480/1500\n",
      "139/139 [==============================] - 0s - loss: 211.6719 - acc: 0.2086 - val_loss: 5.2510 - val_acc: 0.8750\n",
      "Epoch 1481/1500\n",
      "139/139 [==============================] - 0s - loss: 211.5214 - acc: 0.2230 - val_loss: 5.2578 - val_acc: 0.8750\n",
      "Epoch 1482/1500\n",
      "139/139 [==============================] - 0s - loss: 212.1086 - acc: 0.2158 - val_loss: 5.2657 - val_acc: 0.8750\n",
      "Epoch 1483/1500\n",
      "139/139 [==============================] - 0s - loss: 212.2719 - acc: 0.2158 - val_loss: 5.2702 - val_acc: 0.8750\n",
      "Epoch 1484/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4018 - acc: 0.2086 - val_loss: 5.2781 - val_acc: 0.8750\n",
      "Epoch 1485/1500\n",
      "139/139 [==============================] - 0s - loss: 212.2495 - acc: 0.2302 - val_loss: 5.2836 - val_acc: 0.8750\n",
      "Epoch 1486/1500\n",
      "139/139 [==============================] - 0s - loss: 211.5643 - acc: 0.2446 - val_loss: 5.2904 - val_acc: 0.8750\n",
      "Epoch 1487/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4416 - acc: 0.2230 - val_loss: 5.2978 - val_acc: 0.8750\n",
      "Epoch 1488/1500\n",
      "139/139 [==============================] - 0s - loss: 211.6191 - acc: 0.2302 - val_loss: 5.3024 - val_acc: 0.8750\n",
      "Epoch 1489/1500\n",
      "139/139 [==============================] - 0s - loss: 212.0888 - acc: 0.2158 - val_loss: 5.3079 - val_acc: 0.8750\n",
      "Epoch 1490/1500\n",
      "139/139 [==============================] - 0s - loss: 211.5481 - acc: 0.2086 - val_loss: 5.3127 - val_acc: 0.8750\n",
      "Epoch 1491/1500\n",
      "139/139 [==============================] - 0s - loss: 211.9738 - acc: 0.2662 - val_loss: 5.3174 - val_acc: 0.8750\n",
      "Epoch 1492/1500\n",
      "139/139 [==============================] - 0s - loss: 211.3275 - acc: 0.2158 - val_loss: 5.3252 - val_acc: 0.8750\n",
      "Epoch 1493/1500\n",
      "139/139 [==============================] - 0s - loss: 212.1105 - acc: 0.2446 - val_loss: 5.3303 - val_acc: 0.8750\n",
      "Epoch 1494/1500\n",
      "139/139 [==============================] - 0s - loss: 211.4314 - acc: 0.2230 - val_loss: 5.3363 - val_acc: 0.8750\n",
      "Epoch 1495/1500\n",
      "139/139 [==============================] - 0s - loss: 211.4441 - acc: 0.2158 - val_loss: 5.3389 - val_acc: 0.8750\n",
      "Epoch 1496/1500\n",
      "139/139 [==============================] - 0s - loss: 211.3216 - acc: 0.2086 - val_loss: 5.3453 - val_acc: 0.8750\n",
      "Epoch 1497/1500\n",
      "139/139 [==============================] - 0s - loss: 210.9655 - acc: 0.2302 - val_loss: 5.3503 - val_acc: 0.8750\n",
      "Epoch 1498/1500\n",
      "139/139 [==============================] - 0s - loss: 211.8757 - acc: 0.2302 - val_loss: 5.3581 - val_acc: 0.8750\n",
      "Epoch 1499/1500\n",
      "139/139 [==============================] - 0s - loss: 211.8268 - acc: 0.2158 - val_loss: 5.3657 - val_acc: 0.8750\n",
      "Epoch 1500/1500\n",
      "139/139 [==============================] - 0s - loss: 212.4339 - acc: 0.2230 - val_loss: 5.3718 - val_acc: 0.8750\n"
     ]
    }
   ],
   "source": [
    "model = baseline_model()\n",
    "seed = 7\n",
    "np.random.seed(seed)\n",
    "\n",
    "from keras.utils.np_utils import to_categorical\n",
    "\n",
    "history = model.fit(X, y, validation_split=0.1, epochs=1500, batch_size=5, verbose=1,class_weight=class_weight)\n",
    "                    #,callbacks=[EarlyStopping(monitor='val_loss', patience=0)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RSZMmERER0eQn1pXWWjfpGrzA0aNH6z2v3W4nN7f6+Q/jP0vRn3+K6R//QZnMDY3XIDXl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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4aede278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# summarize history for loss\n",
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QtJv+pvRw33379iUqKopPP/2UwsJCrr/+ep544gny8vJ48MEHSUpKwjAMxo8fT2pqKmfO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\nBCGEEMKt/w+Xy2jocfyjtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4bd038d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# summarize history for loss\n",
    "plt.plot(history.history['acc'])\n",
    "plt.plot(history.history['val_acc'])\n",
    "plt.title('model accuracy')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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c1g5wreRRMqrKmkAkqZ7R6XQUFhZSVFRUar6Cu7s7RUVFToyscvUtPiEEKpUK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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4af1cb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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p7/5odejQociyZR0/ANCyZUud48HFxUXn+nP27NkSPwd9zr3iBAUF6cx/+/btEstAXwqF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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4b350b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WLFggGRkZcurUKVm3bp34+flJVFSUVFRUKOvi9wHuFStWyLFjx5RB2s8//1xERLZv3y7/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\nsohhQUREFjEsiIjIIoYFERFZ9P8BK1XgygXS4KEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4b37cb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_data_predicted = model.predict(X).flatten()\n",
    "test_data_reference = y\n",
    "\n",
    "relative_deviation = test_data_predicted/test_data_reference - 1.0\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(range(len(test_data_reference)), test_data_reference, 'b-', label='reference')\n",
    "plt.plot(range(len(test_data_predicted)), test_data_predicted, 'r--', label='predicted')\n",
    "plt.xlabel('test case #')\n",
    "plt.ylabel('predictions')\n",
    "plt.title('Reference values vs predicted values')\n",
    "plt.legend()\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(range(len(test_data_predicted)), relative_deviation, 'bx', label='relative deviation')\n",
    "plt.xlabel('test case #')\n",
    "plt.ylabel('relative deviation')\n",
    "plt.title('Relative deviation of predicted values (predicted / reference - 1)')\n",
    "plt.legend()\n",
    "\n",
    "plt.figure()\n",
    "plt.scatter(test_data_predicted, test_data_reference)\n",
    "plt.title(\"Predicted vs Observed Scatterplot\")\n",
    "plt.xlabel('Observed')\n",
    "plt.ylabel('Predicted')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'model' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-a68e75151f0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mkeras\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvis_utils\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmodel_to_dot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mSVG\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_to_dot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mshow_shapes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mshow_layer_names\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprog\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'dot'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'svg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'model' is not defined"
     ]
    }
   ],
   "source": [
    "from IPython.display import SVG\n",
    "from keras.utils.vis_utils import model_to_dot\n",
    "\n",
    "SVG(model_to_dot(model,show_shapes=True,show_layer_names=False,).create(prog='dot', format='svg'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gSZMmageM5s2bIzU1Fa+++ipMJpO6ycjly5fh6emJ8uXLIzU1Ffv370e/fv3U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h4GDx7MKyLUVE/gsmCa348fPx7Ozs68/bm4uAAoeZE1btyYDQ769++Phw8f8jRtuYX7vQUC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\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yt3XrVkybNo2+16JFC/Ts2ZNuW1dXFyKRCBYWFlAoFJDL5ZRAT5kypdrzxzpAaFZS2SY7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c4d8ea780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_neural_net(ax, left, right, bottom, top, layer_sizes):\n",
    "    n_layers = len(layer_sizes)\n",
    "    v_spacing = (top - bottom)/float(max(layer_sizes))\n",
    "    h_spacing = (right - left)/float(len(layer_sizes) - 1)\n",
    "    # Nodes\n",
    "    for n, layer_size in enumerate(layer_sizes):\n",
    "        layer_top = v_spacing*(layer_size - 1)/2. + (top + bottom)/2.\n",
    "        for m in range(layer_size):\n",
    "            circle = plt.Circle((n*h_spacing + left, layer_top - m*v_spacing), v_spacing/4.,\n",
    "                                color='w', ec='k', zorder=4)\n",
    "            ax.add_artist(circle)\n",
    "    # Edges\n",
    "    for n, (layer_size_a, layer_size_b) in enumerate(zip(layer_sizes[:-1], layer_sizes[1:])):\n",
    "        layer_top_a = v_spacing*(layer_size_a - 1)/2. + (top + bottom)/2.\n",
    "        layer_top_b = v_spacing*(layer_size_b - 1)/2. + (top + bottom)/2.\n",
    "        for m in range(layer_size_a):\n",
    "            for o in range(layer_size_b):\n",
    "                line = plt.Line2D([n*h_spacing + left, (n + 1)*h_spacing + left],\n",
    "                                  [layer_top_a - m*v_spacing, layer_top_b - o*v_spacing], c='k')\n",
    "                ax.add_artist(line)\n",
    "                \n",
    "                \n",
    "fig = plt.figure(figsize=(12, 12))\n",
    "ax = fig.gca()\n",
    "ax.axis('off')\n",
    "draw_neural_net(ax, .1, .9, .1, .9, [16, 10, 5, 1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# # fix random seed for reproducibility\n",
    "# seed = 7\n",
    "# np.random.seed(seed)\n",
    "# # evaluate model with standardized dataset\n",
    "# estimator = KerasClassifier(build_fn=baseline_model, nb_epoch=3000, batch_size=5, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# kfold = KFold(n_splits=20, random_state=seed)\n",
    "# results = cross_val_score(estimator, X, y, cv=kfold)\n",
    "# print(\"Results: %.2f (%.2f) MSE\" % (results.mean(), results.std()))\n",
    "# estimator.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# test_data_predicted = estimator.predict(X).flatten()\n",
    "# test_data_reference = y\n",
    "\n",
    "# plt.scatter(test_data_predicted, test_data_reference)\n",
    "# plt.title(\"Predicted vs Observed Scatterplot\")\n",
    "# plt.xlabel('Observed')\n",
    "# plt.ylabel('Predicted')\n",
    "\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# import pydot\n",
    "# from IPython.display import SVG\n",
    "# from keras.utils.vis_utils import model_to_dot\n",
    "\n",
    "# SVG(model_to_dot(model).create(prog='dot', format='svg'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Y_hat = results.predict(X)\n",
    "# plt.scatter(y, Y_hat)\n",
    "# plt.show()"
   ]
  }
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