Kaggle_Reddit_Multiclass_Classification by Hair Albeiro Parra Barrera is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.. Every unauthorized infraction will be legally prosecuted.

Bernoulli_NB.py by Ashray Mallesh & Hamza Rizwan is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mini-Project 2: Kaggle Reddit multi-class classification

• Project for implementing multi-output classification of reddit data.

Our paper:

• https://drive.google.com/file/d/1PQ20eYt0ywUCgG7qd_r5dn_DSV9kVfRk/view?usp=sharing

Naive Bayes Formulation

See

• https://sklearn.org/modules/naive_bayes.html
• https://www.cs.ubc.ca/~murphyk/Teaching/CS340-Fall07/NB.pdf

Dataset labels distribution

• We observe that the labels have a very well balanced distribution.

Current Best Model: Scikit-learn Multinomial Naive Bayes (Kaggle acc: 57.65,%, local cv acc: 57.10 %)

• Note: The following confussion matrices the original training data which we split it into X_train (63000 samples), X_test (7000 samples), y_train (63000 samples) and y_test(7000) samples. Our second best model comes from the Multinomial Naive Bayes classifier. We display confussion matrix for it:

Kaggle_Reddit_Multiclass_Classification by Hair Albeiro Parra Barrera is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.. Every unauthorized infraction will be legally prosecuted.

Bernoulli_NB.py by Ashray Mallesh & Hamza Rizwan is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.