GitHub - go2chayan/GMM_using_EM: A demo of Gaussian Mixture Model using Expectation Maximization

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A demo of Gaussian Mixture Model using Expectation Maximization

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
README		README
figure_1_4_clusters.png		figure_1_4_clusters.png
figure_2_4_clusters.png		figure_2_4_clusters.png
points.dat		points.dat
progAss4.py		progAss4.py

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README
======

I did it as a part of homework problem in the Machine Learning class taught by Prof Daniel Gildea (https://www.cs.rochester.edu/~gildea/) in Spring 2014. Here I implemented a Gaussian Mixture Model (GMM) Clustering using Expectation Maximization (EM) algorithm.
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Name: Md. Iftekhar Tanveer
Email: itanveer@cs.rochester.edu  or  mtanveer@z.rochester.edu
Course: CS446
Homework: EM algorithm


************** Files ***************
README: This document
progAss2.py: The original python script. Just run the file using python. The main function will automatically called.
voting2.dat: Dataset file

************* Algorithm ************
It is commented well in the code


************* Results **************
4 clusters. pictures attached

************* Interpretations *****
Max possible development likelihood falls if the number of cluster exceeds 4