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Expectation Maximization

Expectation maximization (EM) algorithm implementation using Python.

  1. Assume that we have distributions come from two sets of data points, red and blue.

  2. From those distribution, we can easily guess the correct estimation of the mean and covariance from each distribution.

  1. However, if we do not know the correct mean and covariance, we can start from guessing the mean and covariance such as this.

  1. Then, we can do the EM algorithm to find the correct numbers. For example, we do in the 10 iterations.

  2. After 10 iterations, we can get better numbers for guessing the parameter. We can see it by comparing to the correct numbers.

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