📄 normal.m
字号:
% [ll, f, cl, P] = normal(data, alpha, mu, sigma)
%
% This function serves several purposes:
% - evaluate PDF of normal mixture at each of the data points
% - evaluate log-likelihood of the data under the model (for
% out-of-sample evaluation)
% - return deterministic classification
% - return ``weights" P (probabilistic classification)
%
% INPUT:
% data : data points: n rows (points), d columns (dimensions)
% alpha : component weights (k by 1)
% mu : component means (k by d)
% sigma : component covariance matrices (d by d by k) or (d by d*k)
%
% OUTPUT:
% ll : log likelihood of the data under the model
% f : (n by 1) value of (total) PDF at each of the data points
% cl : (n by 1) deterministic classification of data points
% P : (n by k) probabilistic classification of data points
%
% by Igor Cadez (03/05/99)
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