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semiArtificial  

Generator of Semi-Artificial Data
View on CRAN: Click here


Download and install semiArtificial package within the R console
Install from CRAN:
install.packages("semiArtificial")

Install from Github:
library("remotes")
install_github("cran/semiArtificial")

Install by package version:
library("remotes")
install_version("semiArtificial", "2.4.1")



Attach the package and use:
library("semiArtificial")
Maintained by
Marko Robnik-Sikonja
[Scholar Profile | Author Map]
First Published: 2014-02-26
Latest Update: 2021-09-23
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.
How to cite:
Marko Robnik-Sikonja (2014). semiArtificial: Generator of Semi-Artificial Data. R package version 2.4.1, https://cran.r-project.org/web/packages/semiArtificial. Accessed 28 Feb. 2025.
Previous versions and publish date:
1.1.0 (2014-02-26 00:44), 1.2.0 (2014-03-17 20:36), 2.0.1 (2015-09-04 01:11), 2.2.4 (2017-03-26 18:12), 2.2.5 (2017-03-31 08:13), 2.3.1 (2019-05-31 23:30)
Other packages that cited semiArtificial R package
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Other R packages that semiArtificial depends, imports, suggests or enhances
Complete documentation for semiArtificial
Functions, R codes and Examples using the semiArtificial R package
Some associated functions: cleanData . dataSimilarity . dsClustCompare . newdata . performanceCompare . rbfDataGen . semiArtificial-package . treeEnsemble . 
Some associated R codes: dataQuality.R . densityTree.R . forestDataGen.R . init.R . misc.R . rbfDataGen.R . rndtrees.R .  Full semiArtificial package functions and examples
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