Gaussian Mixture Model
Introduction
Using Expectation Maximization algorithm to implement Gaussian Mixture Model on Old Faithful Dataset. EM algorithm is an iterative optimization technique which is operated locally.Given a Gaussian mixture model, the goal is to maximize
the likelihood function with respect to the parameters
comprising the means and covariances of the components
and the mixing coefficients
EM Algorithm for GMM:
Source: Pattern Recogition and Machine Learning by Christopher Bishop
Results
Iteration 0:
Iteration 1:
Iteration 2:
Iteration 3:
Iteration 4:
Iteration 5:
