tutorial5.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 5 Comparing regressors\n",
    "* https://github.com/dataprofessor/bioinformatics_freecodecamp/blob/main/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb\n",
    "* https://youtu.be/jBlTQjcKuaY?t=4257"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "! pip install lazypredict --quiet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "import lazypredict\n",
    "from lazypredict.Supervised import LazyRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./data/06_bioactivity_data_3class_pubchem_fp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop('pIC50', axis=1)\n",
    "Y = df.pIC50"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(118, 881)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(118, 197)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_selection import VarianceThreshold\n",
    "selection = VarianceThreshold(threshold=(.8 * (1 - .8)))\n",
    "X = selection.fit_transform(X)\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare ML algorithms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 42/42 [00:19<00:00,  2.16it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'tuple' object has no attribute '__name__'\n",
      "Invalid Regressor(s)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 42/42 [00:17<00:00,  2.35it/s]\n"
     ]
    }
   ],
   "source": [
    "# Defines and builds the lazyclassifier\n",
    "clf = LazyRegressor(verbose=0,ignore_warnings=True, custom_metric=None)\n",
    "models_train,predictions_train = clf.fit(X_train, X_train, Y_train, Y_train)\n",
    "models_test,predictions_test = clf.fit(X_train, X_test, Y_train, Y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adjusted R-Squared</th>\n",
       "      <th>R-Squared</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>Time Taken</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Lars</th>\n",
       "      <td>25347642064999155888557517014579731390042007156...</td>\n",
       "      <td>-2834575026623561407401921040492295971014011623...</td>\n",
       "      <td>4192062295205520992030202289217237034205184.00</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KernelRidge</th>\n",
       "      <td>30.77</td>\n",
       "      <td>-32.29</td>\n",
       "      <td>4.54</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QuantileRegressor</th>\n",
       "      <td>1.90</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoLars</th>\n",
       "      <td>1.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DummyRegressor</th>\n",
       "      <td>1.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ElasticNet</th>\n",
       "      <td>1.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lasso</th>\n",
       "      <td>1.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LarsCV</th>\n",
       "      <td>1.76</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrthogonalMatchingPursuitCV</th>\n",
       "      <td>1.57</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoLarsCV</th>\n",
       "      <td>1.49</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KNeighborsRegressor</th>\n",
       "      <td>1.45</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BayesianRidge</th>\n",
       "      <td>1.42</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ElasticNetCV</th>\n",
       "      <td>1.39</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.52</td>\n",
       "      <td>7.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoCV</th>\n",
       "      <td>1.38</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.51</td>\n",
       "      <td>5.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GammaRegressor</th>\n",
       "      <td>1.36</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TweedieRegressor</th>\n",
       "      <td>1.36</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVR</th>\n",
       "      <td>1.34</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NuSVR</th>\n",
       "      <td>1.34</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGBMRegressor</th>\n",
       "      <td>1.32</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassiveAggressiveRegressor</th>\n",
       "      <td>1.31</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HistGradientBoostingRegressor</th>\n",
       "      <td>1.31</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AdaBoostRegressor</th>\n",
       "      <td>1.30</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrthogonalMatchingPursuit</th>\n",
       "      <td>1.27</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoissonRegressor</th>\n",
       "      <td>1.24</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BaggingRegressor</th>\n",
       "      <td>1.23</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SGDRegressor</th>\n",
       "      <td>1.23</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HuberRegressor</th>\n",
       "      <td>1.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RidgeCV</th>\n",
       "      <td>1.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LinearSVR</th>\n",
       "      <td>1.21</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RandomForestRegressor</th>\n",
       "      <td>1.20</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MLPRegressor</th>\n",
       "      <td>1.17</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LinearRegression</th>\n",
       "      <td>1.16</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TransformedTargetRegressor</th>\n",
       "      <td>1.16</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ridge</th>\n",
       "      <td>1.16</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GradientBoostingRegressor</th>\n",
       "      <td>1.16</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XGBRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GaussianProcessRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExtraTreesRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExtraTreeRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DecisionTreeRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                              Adjusted R-Squared  \\\n",
       "Model                                                                              \n",
       "Lars                          25347642064999155888557517014579731390042007156...   \n",
       "KernelRidge                                                                30.77   \n",
       "QuantileRegressor                                                           1.90   \n",
       "LassoLars                                                                   1.89   \n",
       "DummyRegressor                                                              1.89   \n",
       "ElasticNet                                                                  1.89   \n",
       "Lasso                                                                       1.89   \n",
       "LarsCV                                                                      1.76   \n",
       "OrthogonalMatchingPursuitCV                                                 1.57   \n",
       "LassoLarsCV                                                                 1.49   \n",
       "KNeighborsRegressor                                                         1.45   \n",
       "BayesianRidge                                                               1.42   \n",
       "ElasticNetCV                                                                1.39   \n",
       "LassoCV                                                                     1.38   \n",
       "GammaRegressor                                                              1.36   \n",
       "TweedieRegressor                                                            1.36   \n",
       "SVR                                                                         1.34   \n",
       "NuSVR                                                                       1.34   \n",
       "LGBMRegressor                                                               1.32   \n",
       "PassiveAggressiveRegressor                                                  1.31   \n",
       "HistGradientBoostingRegressor                                               1.31   \n",
       "AdaBoostRegressor                                                           1.30   \n",
       "OrthogonalMatchingPursuit                                                   1.27   \n",
       "PoissonRegressor                                                            1.24   \n",
       "BaggingRegressor                                                            1.23   \n",
       "SGDRegressor                                                                1.23   \n",
       "HuberRegressor                                                              1.21   \n",
       "RidgeCV                                                                     1.21   \n",
       "LinearSVR                                                                   1.21   \n",
       "RandomForestRegressor                                                       1.20   \n",
       "MLPRegressor                                                                1.17   \n",
       "LinearRegression                                                            1.16   \n",
       "TransformedTargetRegressor                                                  1.16   \n",
       "Ridge                                                                       1.16   \n",
       "GradientBoostingRegressor                                                   1.16   \n",
       "XGBRegressor                                                                1.15   \n",
       "GaussianProcessRegressor                                                    1.15   \n",
       "ExtraTreesRegressor                                                         1.15   \n",
       "ExtraTreeRegressor                                                          1.15   \n",
       "DecisionTreeRegressor                                                       1.15   \n",
       "\n",
       "                                                                       R-Squared  \\\n",
       "Model                                                                              \n",
       "Lars                          -2834575026623561407401921040492295971014011623...   \n",
       "KernelRidge                                                               -32.29   \n",
       "QuantileRegressor                                                          -0.01   \n",
       "LassoLars                                                                   0.00   \n",
       "DummyRegressor                                                              0.00   \n",
       "ElasticNet                                                                  0.00   \n",
       "Lasso                                                                       0.00   \n",
       "LarsCV                                                                      0.15   \n",
       "OrthogonalMatchingPursuitCV                                                 0.36   \n",
       "LassoLarsCV                                                                 0.45   \n",
       "KNeighborsRegressor                                                         0.49   \n",
       "BayesianRidge                                                               0.53   \n",
       "ElasticNetCV                                                                0.57   \n",
       "LassoCV                                                                     0.58   \n",
       "GammaRegressor                                                              0.60   \n",
       "TweedieRegressor                                                            0.60   \n",
       "SVR                                                                         0.62   \n",
       "NuSVR                                                                       0.62   \n",
       "LGBMRegressor                                                               0.65   \n",
       "PassiveAggressiveRegressor                                                  0.65   \n",
       "HistGradientBoostingRegressor                                               0.65   \n",
       "AdaBoostRegressor                                                           0.67   \n",
       "OrthogonalMatchingPursuit                                                   0.70   \n",
       "PoissonRegressor                                                            0.73   \n",
       "BaggingRegressor                                                            0.74   \n",
       "SGDRegressor                                                                0.74   \n",
       "HuberRegressor                                                              0.76   \n",
       "RidgeCV                                                                     0.76   \n",
       "LinearSVR                                                                   0.77   \n",
       "RandomForestRegressor                                                       0.78   \n",
       "MLPRegressor                                                                0.80   \n",
       "LinearRegression                                                            0.82   \n",
       "TransformedTargetRegressor                                                  0.82   \n",
       "Ridge                                                                       0.82   \n",
       "GradientBoostingRegressor                                                   0.82   \n",
       "XGBRegressor                                                                0.83   \n",
       "GaussianProcessRegressor                                                    0.83   \n",
       "ExtraTreesRegressor                                                         0.83   \n",
       "ExtraTreeRegressor                                                          0.83   \n",
       "DecisionTreeRegressor                                                       0.83   \n",
       "\n",
       "                                                                        RMSE  \\\n",
       "Model                                                                          \n",
       "Lars                          4192062295205520992030202289217237034205184.00   \n",
       "KernelRidge                                                             4.54   \n",
       "QuantileRegressor                                                       0.79   \n",
       "LassoLars                                                               0.79   \n",
       "DummyRegressor                                                          0.79   \n",
       "ElasticNet                                                              0.79   \n",
       "Lasso                                                                   0.79   \n",
       "LarsCV                                                                  0.72   \n",
       "OrthogonalMatchingPursuitCV                                             0.63   \n",
       "LassoLarsCV                                                             0.58   \n",
       "KNeighborsRegressor                                                     0.56   \n",
       "BayesianRidge                                                           0.54   \n",
       "ElasticNetCV                                                            0.52   \n",
       "LassoCV                                                                 0.51   \n",
       "GammaRegressor                                                          0.50   \n",
       "TweedieRegressor                                                        0.50   \n",
       "SVR                                                                     0.49   \n",
       "NuSVR                                                                   0.48   \n",
       "LGBMRegressor                                                           0.47   \n",
       "PassiveAggressiveRegressor                                              0.47   \n",
       "HistGradientBoostingRegressor                                           0.46   \n",
       "AdaBoostRegressor                                                       0.45   \n",
       "OrthogonalMatchingPursuit                                               0.43   \n",
       "PoissonRegressor                                                        0.41   \n",
       "BaggingRegressor                                                        0.40   \n",
       "SGDRegressor                                                            0.40   \n",
       "HuberRegressor                                                          0.39   \n",
       "RidgeCV                                                                 0.38   \n",
       "LinearSVR                                                               0.38   \n",
       "RandomForestRegressor                                                   0.37   \n",
       "MLPRegressor                                                            0.35   \n",
       "LinearRegression                                                        0.33   \n",
       "TransformedTargetRegressor                                              0.33   \n",
       "Ridge                                                                   0.33   \n",
       "GradientBoostingRegressor                                               0.33   \n",
       "XGBRegressor                                                            0.32   \n",
       "GaussianProcessRegressor                                                0.32   \n",
       "ExtraTreesRegressor                                                     0.32   \n",
       "ExtraTreeRegressor                                                      0.32   \n",
       "DecisionTreeRegressor                                                   0.32   \n",
       "\n",
       "                               Time Taken  \n",
       "Model                                      \n",
       "Lars                                 0.12  \n",
       "KernelRidge                          0.02  \n",
       "QuantileRegressor                    0.31  \n",
       "LassoLars                            0.03  \n",
       "DummyRegressor                       0.02  \n",
       "ElasticNet                           0.02  \n",
       "Lasso                                0.03  \n",
       "LarsCV                               0.44  \n",
       "OrthogonalMatchingPursuitCV          0.03  \n",
       "LassoLarsCV                          0.10  \n",
       "KNeighborsRegressor                  0.08  \n",
       "BayesianRidge                        0.06  \n",
       "ElasticNetCV                         7.54  \n",
       "LassoCV                              5.70  \n",
       "GammaRegressor                       0.53  \n",
       "TweedieRegressor                     0.55  \n",
       "SVR                                  0.03  \n",
       "NuSVR                                0.02  \n",
       "LGBMRegressor                        0.03  \n",
       "PassiveAggressiveRegressor           0.02  \n",
       "HistGradientBoostingRegressor        0.09  \n",
       "AdaBoostRegressor                    0.09  \n",
       "OrthogonalMatchingPursuit            0.02  \n",
       "PoissonRegressor                     0.89  \n",
       "BaggingRegressor                     0.03  \n",
       "SGDRegressor                         0.04  \n",
       "HuberRegressor                       0.06  \n",
       "RidgeCV                              0.04  \n",
       "LinearSVR                            0.09  \n",
       "RandomForestRegressor                0.22  \n",
       "MLPRegressor                         0.19  \n",
       "LinearRegression                     0.04  \n",
       "TransformedTargetRegressor           0.04  \n",
       "Ridge                                0.02  \n",
       "GradientBoostingRegressor            0.13  \n",
       "XGBRegressor                         1.36  \n",
       "GaussianProcessRegressor             0.04  \n",
       "ExtraTreesRegressor                  0.19  \n",
       "ExtraTreeRegressor                   0.04  \n",
       "DecisionTreeRegressor                0.04  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Performance table of the training set (80% subset)\n",
    "predictions_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adjusted R-Squared</th>\n",
       "      <th>R-Squared</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>Time Taken</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Lars</th>\n",
       "      <td>42483102471082319590032533436736554213229795525...</td>\n",
       "      <td>-3213939056507966539693088870217573824749714660...</td>\n",
       "      <td>22990410431363096810474668739427162037982589843...</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TransformedTargetRegressor</th>\n",
       "      <td>60027498939360271663104.00</td>\n",
       "      <td>-454121078932551577370624.00</td>\n",
       "      <td>864198954039.51</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LinearRegression</th>\n",
       "      <td>60027498939360271663104.00</td>\n",
       "      <td>-454121078932551577370624.00</td>\n",
       "      <td>864198954039.51</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KernelRidge</th>\n",
       "      <td>3.04</td>\n",
       "      <td>-14.40</td>\n",
       "      <td>5.03</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GaussianProcessRegressor</th>\n",
       "      <td>2.23</td>\n",
       "      <td>-8.34</td>\n",
       "      <td>3.92</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoLars</th>\n",
       "      <td>1.15</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DummyRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ElasticNet</th>\n",
       "      <td>1.15</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lasso</th>\n",
       "      <td>1.15</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QuantileRegressor</th>\n",
       "      <td>1.15</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>1.35</td>\n",
       "      <td>0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XGBRegressor</th>\n",
       "      <td>1.14</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>1.31</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrthogonalMatchingPursuit</th>\n",
       "      <td>1.14</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>1.30</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LarsCV</th>\n",
       "      <td>1.13</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>1.29</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LinearSVR</th>\n",
       "      <td>1.13</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.28</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassiveAggressiveRegressor</th>\n",
       "      <td>1.13</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HuberRegressor</th>\n",
       "      <td>1.12</td>\n",
       "      <td>0.06</td>\n",
       "      <td>1.24</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ridge</th>\n",
       "      <td>1.12</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MLPRegressor</th>\n",
       "      <td>1.11</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BaggingRegressor</th>\n",
       "      <td>1.11</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.16</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SGDRegressor</th>\n",
       "      <td>1.11</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GradientBoostingRegressor</th>\n",
       "      <td>1.11</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RidgeCV</th>\n",
       "      <td>1.11</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoLarsCV</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoissonRegressor</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.24</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExtraTreeRegressor</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.11</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DecisionTreeRegressor</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.11</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGBMRegressor</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ExtraTreesRegressor</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ElasticNetCV</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.09</td>\n",
       "      <td>7.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LassoCV</th>\n",
       "      <td>1.10</td>\n",
       "      <td>0.28</td>\n",
       "      <td>1.09</td>\n",
       "      <td>5.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HistGradientBoostingRegressor</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AdaBoostRegressor</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NuSVR</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GammaRegressor</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RandomForestRegressor</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVR</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrthogonalMatchingPursuitCV</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TweedieRegressor</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BayesianRidge</th>\n",
       "      <td>1.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KNeighborsRegressor</th>\n",
       "      <td>1.07</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                              Adjusted R-Squared  \\\n",
       "Model                                                                              \n",
       "Lars                          42483102471082319590032533436736554213229795525...   \n",
       "TransformedTargetRegressor                            60027498939360271663104.00   \n",
       "LinearRegression                                      60027498939360271663104.00   \n",
       "KernelRidge                                                                 3.04   \n",
       "GaussianProcessRegressor                                                    2.23   \n",
       "LassoLars                                                                   1.15   \n",
       "DummyRegressor                                                              1.15   \n",
       "ElasticNet                                                                  1.15   \n",
       "Lasso                                                                       1.15   \n",
       "QuantileRegressor                                                           1.15   \n",
       "XGBRegressor                                                                1.14   \n",
       "OrthogonalMatchingPursuit                                                   1.14   \n",
       "LarsCV                                                                      1.13   \n",
       "LinearSVR                                                                   1.13   \n",
       "PassiveAggressiveRegressor                                                  1.13   \n",
       "HuberRegressor                                                              1.12   \n",
       "Ridge                                                                       1.12   \n",
       "MLPRegressor                                                                1.11   \n",
       "BaggingRegressor                                                            1.11   \n",
       "SGDRegressor                                                                1.11   \n",
       "GradientBoostingRegressor                                                   1.11   \n",
       "RidgeCV                                                                     1.11   \n",
       "LassoLarsCV                                                                 1.10   \n",
       "PoissonRegressor                                                            1.10   \n",
       "ExtraTreeRegressor                                                          1.10   \n",
       "DecisionTreeRegressor                                                       1.10   \n",
       "LGBMRegressor                                                               1.10   \n",
       "ExtraTreesRegressor                                                         1.10   \n",
       "ElasticNetCV                                                                1.10   \n",
       "LassoCV                                                                     1.10   \n",
       "HistGradientBoostingRegressor                                               1.09   \n",
       "AdaBoostRegressor                                                           1.09   \n",
       "NuSVR                                                                       1.09   \n",
       "GammaRegressor                                                              1.09   \n",
       "RandomForestRegressor                                                       1.09   \n",
       "SVR                                                                         1.09   \n",
       "OrthogonalMatchingPursuitCV                                                 1.09   \n",
       "TweedieRegressor                                                            1.09   \n",
       "BayesianRidge                                                               1.09   \n",
       "KNeighborsRegressor                                                         1.07   \n",
       "\n",
       "                                                                       R-Squared  \\\n",
       "Model                                                                              \n",
       "Lars                          -3213939056507966539693088870217573824749714660...   \n",
       "TransformedTargetRegressor                          -454121078932551577370624.00   \n",
       "LinearRegression                                    -454121078932551577370624.00   \n",
       "KernelRidge                                                               -14.40   \n",
       "GaussianProcessRegressor                                                   -8.34   \n",
       "LassoLars                                                                  -0.14   \n",
       "DummyRegressor                                                             -0.14   \n",
       "ElasticNet                                                                 -0.14   \n",
       "Lasso                                                                      -0.14   \n",
       "QuantileRegressor                                                          -0.10   \n",
       "XGBRegressor                                                               -0.04   \n",
       "OrthogonalMatchingPursuit                                                  -0.02   \n",
       "LarsCV                                                                     -0.01   \n",
       "LinearSVR                                                                   0.01   \n",
       "PassiveAggressiveRegressor                                                  0.05   \n",
       "HuberRegressor                                                              0.06   \n",
       "Ridge                                                                       0.09   \n",
       "MLPRegressor                                                                0.17   \n",
       "BaggingRegressor                                                            0.18   \n",
       "SGDRegressor                                                                0.19   \n",
       "GradientBoostingRegressor                                                   0.20   \n",
       "RidgeCV                                                                     0.20   \n",
       "LassoLarsCV                                                                 0.23   \n",
       "PoissonRegressor                                                            0.24   \n",
       "ExtraTreeRegressor                                                          0.25   \n",
       "DecisionTreeRegressor                                                       0.26   \n",
       "LGBMRegressor                                                               0.26   \n",
       "ExtraTreesRegressor                                                         0.27   \n",
       "ElasticNetCV                                                                0.27   \n",
       "LassoCV                                                                     0.28   \n",
       "HistGradientBoostingRegressor                                               0.29   \n",
       "AdaBoostRegressor                                                           0.30   \n",
       "NuSVR                                                                       0.31   \n",
       "GammaRegressor                                                              0.31   \n",
       "RandomForestRegressor                                                       0.31   \n",
       "SVR                                                                         0.32   \n",
       "OrthogonalMatchingPursuitCV                                                 0.32   \n",
       "TweedieRegressor                                                            0.32   \n",
       "BayesianRidge                                                               0.32   \n",
       "KNeighborsRegressor                                                         0.47   \n",
       "\n",
       "                                                                            RMSE  \\\n",
       "Model                                                                              \n",
       "Lars                          22990410431363096810474668739427162037982589843...   \n",
       "TransformedTargetRegressor                                       864198954039.51   \n",
       "LinearRegression                                                 864198954039.51   \n",
       "KernelRidge                                                                 5.03   \n",
       "GaussianProcessRegressor                                                    3.92   \n",
       "LassoLars                                                                   1.37   \n",
       "DummyRegressor                                                              1.37   \n",
       "ElasticNet                                                                  1.37   \n",
       "Lasso                                                                       1.37   \n",
       "QuantileRegressor                                                           1.35   \n",
       "XGBRegressor                                                                1.31   \n",
       "OrthogonalMatchingPursuit                                                   1.30   \n",
       "LarsCV                                                                      1.29   \n",
       "LinearSVR                                                                   1.28   \n",
       "PassiveAggressiveRegressor                                                  1.25   \n",
       "HuberRegressor                                                              1.24   \n",
       "Ridge                                                                       1.22   \n",
       "MLPRegressor                                                                1.17   \n",
       "BaggingRegressor                                                            1.16   \n",
       "SGDRegressor                                                                1.15   \n",
       "GradientBoostingRegressor                                                   1.15   \n",
       "RidgeCV                                                                     1.14   \n",
       "LassoLarsCV                                                                 1.13   \n",
       "PoissonRegressor                                                            1.12   \n",
       "ExtraTreeRegressor                                                          1.11   \n",
       "DecisionTreeRegressor                                                       1.11   \n",
       "LGBMRegressor                                                               1.10   \n",
       "ExtraTreesRegressor                                                         1.10   \n",
       "ElasticNetCV                                                                1.09   \n",
       "LassoCV                                                                     1.09   \n",
       "HistGradientBoostingRegressor                                               1.08   \n",
       "AdaBoostRegressor                                                           1.07   \n",
       "NuSVR                                                                       1.07   \n",
       "GammaRegressor                                                              1.06   \n",
       "RandomForestRegressor                                                       1.06   \n",
       "SVR                                                                         1.06   \n",
       "OrthogonalMatchingPursuitCV                                                 1.06   \n",
       "TweedieRegressor                                                            1.06   \n",
       "BayesianRidge                                                               1.05   \n",
       "KNeighborsRegressor                                                         0.94   \n",
       "\n",
       "                               Time Taken  \n",
       "Model                                      \n",
       "Lars                                 0.09  \n",
       "TransformedTargetRegressor           0.02  \n",
       "LinearRegression                     0.02  \n",
       "KernelRidge                          0.02  \n",
       "GaussianProcessRegressor             0.04  \n",
       "LassoLars                            0.02  \n",
       "DummyRegressor                       0.03  \n",
       "ElasticNet                           0.02  \n",
       "Lasso                                0.03  \n",
       "QuantileRegressor                    0.27  \n",
       "XGBRegressor                         0.12  \n",
       "OrthogonalMatchingPursuit            0.02  \n",
       "LarsCV                               0.43  \n",
       "LinearSVR                            0.08  \n",
       "PassiveAggressiveRegressor           0.02  \n",
       "HuberRegressor                       0.06  \n",
       "Ridge                                0.03  \n",
       "MLPRegressor                         0.19  \n",
       "BaggingRegressor                     0.03  \n",
       "SGDRegressor                         0.06  \n",
       "GradientBoostingRegressor            0.12  \n",
       "RidgeCV                              0.04  \n",
       "LassoLarsCV                          0.08  \n",
       "PoissonRegressor                     1.01  \n",
       "ExtraTreeRegressor                   0.02  \n",
       "DecisionTreeRegressor                0.04  \n",
       "LGBMRegressor                        0.03  \n",
       "ExtraTreesRegressor                  0.20  \n",
       "ElasticNetCV                         7.70  \n",
       "LassoCV                              5.35  \n",
       "HistGradientBoostingRegressor        0.08  \n",
       "AdaBoostRegressor                    0.08  \n",
       "NuSVR                                0.02  \n",
       "GammaRegressor                       0.47  \n",
       "RandomForestRegressor                0.22  \n",
       "SVR                                  0.01  \n",
       "OrthogonalMatchingPursuitCV          0.03  \n",
       "TweedieRegressor                     0.69  \n",
       "BayesianRidge                        0.03  \n",
       "KNeighborsRegressor                  0.06  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Performance table of the test set (20% subset)\n",
    "predictions_test"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data visualization of model performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.0, 40.0)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(5, 10))\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "ax = sns.barplot(y=predictions_train.index, x=\"R-Squared\", data=predictions_train)\n",
    "ax.set(xlim=(0, 1))\n",
    "plt.ylim(-1,len(predictions_train.index))\n",
    "#plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.0, 40.0)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 10))\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "ax = sns.barplot(y=predictions_train.index, x=\"RMSE\", data=predictions_train)\n",
    "ax.set(xlim=(0, 5))\n",
    "plt.ylim(-1,len(predictions_train.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 10.0)]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 10))\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "ax = sns.barplot(y=predictions_train.index, x=\"Time Taken\", data=predictions_train)\n",
    "ax.set(xlim=(0, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "drug-discovery",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}