semiArtificial: Generator of semi-artificial data

Package semiArtificial contains methods to generate and evaluate semi-artificial data sets. Based on a given data set different methods learn data properties using machine learning algorithms and generate new data with the same properties. The package currently includes the following data generator: -a RBF network based generator using rbfDDA from RSNNS package. More generators are planned in near future. Data evaluation support tools include: -single attribute based statistical evaluation: mean, median,standard deviation, skewness, kurtosis, KS test, Hellinger distance -evaluation based on clustering using Adjusted Rand Index (ARI) -evaluation based on classification performance with various learning models, eg, random forests.

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