Returns log-likelihood values and indices of the most probable mixture component for given samples

[logLikelihoods, labels, probs] = model.predict2(sample)

Input

• samples Samples for classification. It should be a one-channel matrix of size nsamples-by-dims with each row representing one sample.

Output

• logLikelihoods Output vector that contains a likelihood logarithm value for each sample. It has nsamples-by-1 size and double type.
• labels Output "class label" for each sample: labels_i = argmax_{k}(p_{i,k}), i=1..N (indices of the most probable mixture component for each sample). It has nsamples-by-1 size and double type.
• probs Optional output matrix that contains posterior probabilities of each mixture component given the sample. It has nsamples-by-ClustersNumber size and double type.