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Machine Learning Study Node - Clustering

Last updated: 2017-10-10 15:39:14 PDT.

In parameteric approaches, we assume the samples are drawn from the a same parametric distribution. This is rarely the case. Now we relax this assumption and assume the samples are from one of a number of distributions.

This approach is called semiparametric density estimation.

### Mixture densitie

The ** mixture density** is defined as

where are the ** mixture components**. They are also called

**. are called**

*clusters***and are called**

*component densities***. The number of parameters is a hyperparameter.**

*mixture proportions*Within each cluster is a parameteric distribution. The samples are assumed to be iid.