Machine Learning

This project contains the implementation of several Supervised Machine Learning Models most of them being implemented from scratch.

These Models include the following :

• Linear Regression
• k-NN Classification (no K-D trees, LSH, Inverted Lists)
• Logistic Regression (One-vs-All approach)
• Decision Trees
• Support Vector Machines (SVM)
• Decision Trees (for input data in ARFF Format)
• Naive Bayes Classifier
• Random Forest Classifier
• Locally Weighted Regression (with alternative of regression trees)
• Preprocessing the Data and applying Regularization
• Boosting