Classifier for SFA demos
Description
Train or apply a Gaussian classifier..
Usage
1  gaussClassifier(gauss, y, realC, method = "train")

Arguments
gauss 
List created by gaussCreate. Contains also the elements:

y 
K x M matrix where K is the total number of patterns and M is the number of variables used for classification. I.e. each row of y contains the data for one pattern. 
realC 
1 x K matrix with NCLASS distinct real class labels needed only for method='train'. In case of method="apply" realC is not used and can have any value 
method 
either "train" (default) or "apply" 
Value
list gauss
containing
gauss$predC 
1 x K matrix: the predicted class 
gauss$prob 
K x NCLASS matrix: prob(k,n) is the estimated probability that pattern k belongs to class m 
See Also
gaussCreate