The complete algorithm (which is fully described in Mastering Machine Learning Algorithms, by Bonaccorso G., Packt Publishing, 2018) is a little more complex than k-means, and it requires deeper mathematical knowledge. As the scope of this book is more practical, we are only discussing the main steps, without providing formal evidence.
Let's start by considering a dataset, X, containing n samples:
Given k distributions, we need to find the weights, wj, and the parameters of each Gaussian (μj, Σj), with the following condition:
This last condition is necessary to maintain consistency with the laws of probability. ...
