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.