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Generation of a very large dataset

    [A,U] = GENDATV(M,C,K,R,T)
    A = GENDATV(M,U)

 M Number of objects to be generated (def. 10^4)
 C Number of classes (def. 10^2)
 K Number of features (def 10)
 R std. dev of class distributions (def 1)
 S Std. dev. of class priors (def 0)
 U Dataset with class means, class priors and R

 A C-class dataset with M objects and K features
 U Dataset with class means, class priors and R


This routine generates an arbitrarily large dataset of C classes by first  generating the class means from a standard K-dimensional normal  distribution. The class priors are genetated from a N(1,S) distribution,  After that their sum is normalized to one. The classes themselves have  spherical normal distributions with an equal standard deviation R for all  features and all classes.

In U the class means, the class priors and R are returned, such that  similar data from the same distribution can be generated.

See also

datasets, prdatasets,

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PRTools User Guide

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