Package: semiArtificial
Title: Generator of Semi-Artificial Data
Version: 2.4.1
Date: 2021-09-23
Author: Marko Robnik-Sikonja
Maintainer: Marko Robnik-Sikonja <marko.robnik@fri.uni-lj.si>
Description: 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 generators:
  i) a RBF network based generator using rbfDDA() from package 'RSNNS',
  ii) a Random Forest based generator for both classification and regression problems
  iii) a density forest based generator for unsupervised data
 Data evaluation support tools include:
  a) single attribute based statistical evaluation: mean, median, standard deviation, skewness, kurtosis, medcouple, L/RMC, KS test, Hellinger distance
  b) evaluation based on clustering using Adjusted Rand Index (ARI) and FM
  c) evaluation based on classification performance with various learning models, e.g., random forests.
License: GPL-3
URL: http://lkm.fri.uni-lj.si/rmarko/software/
Imports: CORElearn (>=
        1.50.3),RSNNS,MASS,nnet,cluster,fpc,stats,timeDate,robustbase,ks,logspline,methods,mcclust,flexclust,StatMatch
NeedsCompilation: no
Packaged: 2021-09-23 19:34:31 UTC; marko
Repository: CRAN
Date/Publication: 2021-09-23 20:10:02 UTC
Built: R 4.6.0; ; 2026-04-29 07:47:24 UTC; unix
