Generation of a simple classification problem of 2 Gaussian classes
A = GENDATS (N,K,D,LABTYPE)
Generation of a K-dimensional 2-class dataset A of N objects. Both classes are Gaussian distributed with identity matrix as covariance matrix. Their means are on a distance D. Class priors are P(1) = P(2) = 0.5.
If N is a vector of sizes, exactly N(I) objects are generated for class I, I = 1,2.
LABTYPE defines the desired label type: 'crisp' or 'soft'. In the latter case true posterior probabilities are set for the labels.