Course: Data Mining and Knowledge Discovery (Fall 2021)
Task: Write own code
... an expectation-maximization (EM) algorithm is a framework that approaches maximum likelihood or maximum a posteriori estimates of parameters in statistical models. In the context of fuzzy or probabilistic model-based clustering, an EM algorithm starts with an initial set of parameters and iterates until the clustering cannot be improved, that is, until the clustering converges or the change is sufficiently small (less than a preset threshold).
J. Han, Jian Pei, and Micheline Kamber, Data mining: concepts and techniques. S.l: Elsevier Science, 2011.
