DataGen: a generator of datasets for evaluation of classification algorithms

Authors:
Dmitri A. Rachkovskij;Ernst M. Kussul
Affiliations:
-;-
Venue:
Pattern Recognition Letters
Year:
1998

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Abstract

Dataset generators are useful for the evaluation of an algorithm's performance because they allow control of the characteristics and amount of data used for benchmarking. We propose a dataset generator called DataGen that allows varying the number of input features and output classes, the complexity and realizations of class regions, the distributions of data samples, the noise level, the number of data samples. A C language listing of basic DataGen version is provided.