Machine Learning

ML algorithms implemented in python from scratch. No machine learning library used.

Decision Tree

Perform classification using Decision Tree on a simplified version of the Titanic dataset. Used information-gain as the splitting criterion.

Naive Bayes Classifier

Perform classification using Naive Bayes with Laplacian Smoothing.

AdaBoost Classifier

Perform classification by implementing adaptive boosting decision tree stubs (Titanic dataset). Used information-gain as the splitting criterion.

K-Means Clustering

Perform unsupervised clustering of the Iris Dataset, with 3 clusters. Evaluated the model by calculating the Jaccard Similarity Index for each cluster formed.