This page is dedicated to analyzation of different ML model I had to make in Data Mining and Machine Learning course at CMI.

Assignment 1 Report

<aside> 💡 This is the evaluation metrics of different ML model fitted on UCI Banking Dataset

train_whtd_rcl test_whtd_rcl test_acc test_prec test_roc time_to_train (ns) model_size (KB)
DTclf 0.901719 0.902602 0.902602 0.643432 0.631061 6.80573e+07 5.63574
gnb 0.870637 0.869002 0.869002 0.412993 0.671698 3.07792e+07 2.31738
mnb 0.889071 0.891881 0.891881 0.52505 0.636322 1.21876e+07 2.33496
bnb 0.876651 0.878938 0.878938 0.443425 0.643411 2.26029e+07 2.35254

DT Classifier

DT Classifier

Gaussian NB

Gaussian NB

Multinomial NB

Multinomial NB

Binomial NB

Binomial NB

</aside>

<aside> 💡 This is the evaluation metrics of different ML model fitted on Bollywood Movies Dataset

train_whtd_rcl test_whtd_rcl test_acc test_prec test_roc time_to_train (ns) model_size (KB)
DTclf 0.818125 0.805882 0.805882 0.705882 0.714669 3.8615e+06 3.63965
gnb 0.784241 0.785294 0.785294 0.818182 0.631422 2.5081e+06 1.68262
mnb 0.749677 0.758824 0.758824 0.571429 0.682148 1.6352e+06 1.7002
bnb 0.722374 0.761765 0.761765 0.614035 0.641455 2.5861e+06 1.71777

DT Classifier

DT Classifier

Gaussian NB

Gaussian NB

Multinomial NB

Multinomial NB

Binomial NB

Binomial NB

</aside>

Assignment 2 Report