This repository includes the implementation of machine learning algorithms (Classification, Clustering, Ensemble Method) learnt in Professor Nicholas Ruozzi's Machine Learning Class (http://www.utdallas.edu/~nrr150130/cs6375/2015fa/index.html).

The following algorithms have been implemented:

• Gradient Descent (Matlab)
• Coordinate Descent (Java)
• Support Vector Machine (Matlab)
• Decision Tree (Java)
• Naive Bayes (Java)
• Logistic Regression (Java)
• Bayesian Network Structure Learning - Chowliu Tree(Java)
• Bayesian Network Parameter Learning (Java)
• Adaboost (Java)
• Value iteration for Markov Decision Process (Java)
• Spectral Clustering (Matlab)

All the Java code are organized in packages, training and testing samples are in ./data folder. A driver class is provided for each algorithm implemented, it is called "*Test.java". To test an algorithm, run:

javac src/package_name/*Test.java
java bin//package_name/*Test

from the command line.