[The Elements of Statistical Learning] 1. Mixture model: describe the data using mix of multiple simple models (ex: gaussian model)Ex) two-component mixture model Y: combination of two gaussian modelsg(y): density of Y-> sum the log g(y) of N data points -> maximize this log-likelihood Parameters of the model: pi, mu1, s1, mu2, s2 => mixture models -> useful for supervised learning, lead to radi..