{ "_id": "6a1f0d57b401979e7341d003", "Package": "semiArtificial", "Title": "Generator of Semi-Artificial Data", "Version": "2.4.1", "Date": "2021-09-23", "Author": "Marko Robnik-Sikonja", "Maintainer": "Marko Robnik-Sikonja ", "Description": "Contains methods to generate and evaluate semi-artificial\ndata sets. Based on a given data set different methods learn\ndata properties using machine learning algorithms and generate\nnew data with the same properties. The package currently\nincludes the following data generators: i) a RBF network based\ngenerator using rbfDDA() from package 'RSNNS', ii) a Random\nForest based generator for both classification and regression\nproblems iii) a density forest based generator for unsupervised\ndata Data evaluation support tools include: a) single attribute\nbased statistical evaluation: mean, median, standard deviation,\nskewness, kurtosis, medcouple, L/RMC, KS test, Hellinger\ndistance b) evaluation based on clustering using Adjusted Rand\nIndex (ARI) and FM c) evaluation based on classification\nperformance with various learning models, e.g., random forests.", "License": "GPL-3", "URL": "http://lkm.fri.uni-lj.si/rmarko/software/", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-17 09:12:39 UTC", "User": "root" }, "Config/pak/sysreqs": "make", "Repository": "https://rmarko.r-universe.dev", "Date/Publication": "2021-09-23 19:10:02 UTC", "RemoteUrl": "https://github.com/cran/semiArtificial", 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