Mixture models
نویسنده
چکیده
where K is the (fixed) number of mixture component, π is a vector of mixing weights, and p(x|k) are the densities for each component. We consider some examples below. 2 Gaussian mixture models Consider the dataset of height and weight in Figure 1. It is clear that there are two subpopulations in this data set, and in this case they are easy to interpret: one represents males and the other females. Within each class or cluster, the data is fairly well represented by a 2D Gaussian (as can be seen from the fitted ellipses), but to model the data as a whole, we need to use a mixture of Gaussians (MoG) or a Gaussian mixture model (GMM). This is defined as follows: p(x|θ) = K
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