rSFA (version 1.00)

gaussClassifier: Classifier for SFA demos

Description

Train or apply a Gaussian classifier..

Usage

gaussClassifier(gauss, y, realC, method = "train")

Arguments

gauss

List created by gaussCreate. Contains also the elements: aligned =0: do not align the Gaussian classifiers with axes, use full covariance matrix =1 (default): set the off-diagonals in covariance matrix to 0, i.e. the Gaussian cla

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 - 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

References

gaussCreate