GENDATS

Generation of a simple classification problem of 2 Gaussian classes

    A = GENDATS (N,K,D,LABTYPE)

Input
N	Dataset size, or 2-element array of class sizes (default: [50 50]).
K	Dimensionality of the dataset to be generated (default: 2).
D	Distance between class means in the first dimension (default: 1).
LABTYPE	Label type to generate, 'crisp' or 'soft' (default: 'crisp').

Output
A	Dataset.

Description

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.

See also

datasets, prdatasets,