Machine Learning Algorithms

These implementations were done as part of assignments of the Machine Learning course ELL409(2018-19) @ IIT Delhi

This project consists of the tasks of building up different kinds of classifiers on various example datasets. PFA : Detailed report for data analysis on FMNIST, Railway Data, Health Data and River Data.

We have implemented following types of Classification schemes for each problem

1. Bayes Classifier (with different class conditional densities and estimation techniques)
2. Naive Bayes Classifier
3. K-means Clustering
4. K-Nearest Neighbor Classifier
5. Principal component analysis (where ever applicable)
6. Linear Models for Binary Classification, Regression and Multi-Class Classification
7. Logistic Models for Binary and Multi-Class Classification
8. Binary and Multi-Class FLDA
9. Perceptron ALgorithm
10. Support Vector Machine