GMM based Expectation Maximization Algorithm.zip

Program find the parameters of GMM model using EM algorithm and labels the data into classes

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The code consist of the implementation of model based technique for data labelling or clustering.Each element of data is considered as random variable whose probability distribution function is Gaussian.In order to estimate model parameters EM is used to maximize the log likelihood of given data set.
Gaussian parameters obtained using EM algorithm are further used to calculate probabilities of data values for every class.And finally on the basis of maximum probability data values are labeled into classes.

Cite As

Mohammad Asif Khan (2026). GMM based Expectation Maximization Algorithm.zip (https://in.mathworks.com/matlabcentral/fileexchange/46727-gmm-based-expectation-maximization-algorithm-zip), MATLAB Central File Exchange. Retrieved .

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General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.4.0.0

Code is optimized.

1.3.0.0

Code is optimized.

1.2.0.0

Code is optimized and takes lesser time to execute.

1.0.0.0