ASE-24

Homeworks

CSC 591(021) Group-15

Steps to run the program

for w2

cd src
python gate.py -f ../data/filename -t stats

for w3

cd src

• To run task 3 of running Naive Bayes Classifier on diabetes.csv

python gate.py -t diabetes 

• To run task 4 of running Naive Bayes Classifier on diabetes.csv using two loops that explore low frequency settings $k \in {0,1,2,3}$ and $m \in {0,1,2,3}$. .

python gate.py -t diabetes-elfs

• To run task 4 of running Naive Bayes Classifier on soybean.csv using two loops that explore low frequency settings $k \in {0,1,2,3}$ and $m \in {0,1,2,3}$.

python gate.py -t soybean 

On experimenting with different values of k and m, we observed that the accuracies for the diabetes dataset does not change, whereas for the soybean dataset the m value of 1 (for $k \in {0,1,2,3}$) yields the highest accuracies.

The reports have been addded in w3

for w4

cd src

• To run Homework 4 task of running Sequential model optimization

python gate.py -t SMO

for w5

cd src

• To run Homework 5 "Get Distance" task,

python gate.py -t dist

• To run Homework 5 "Get Far" task,

python gate.py -t far

for w6

cd src

• To run Homework 6 "doubletap" task,

python gate.py -t doubletap

• To run Homework 6 "tree" task,

python gate.py -t tree

• To run Homework 6 "Half" task,

python gate.py -t half

• To run Homework 6 "Branch" task,

python gate.py -t far

for w7

cd src

• To run Homework 7 "Part1 (no stats)" task,

python gate.py -t generatestats

• To run Homework 7 "Part Two (stats)" task,

python gate.py -t experimenttreatments

for w8

cd src

• To run Homework 8 "Discretization" task,

python gate.py -t bin

for w9

cd src

• To run Homework 8 "Rules" task,

python gate.py -t rule

✨ Contributors

Dhiraj Venugopal

Sharat Neppali

SoundaryaKhanapur