Package: RaSEn 3.0.0

RaSEn: Random Subspace Ensemble Classification and Variable Screening

We propose a general ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing extended Bayesian information criterion (eBIC), minimizing training error, minimizing the validation error, minimizing the cross-validation error, minimizing leave-one-out error. There are various choices of base classifier, for instance, linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, logistic regression, decision trees, random forest, support vector machines. RaSE algorithm can also be applied to do feature ranking, providing us the importance of each feature based on the selected percentage in multiple subspaces. RaSE framework can be extended to the general prediction framework, including both classification and regression. We can use the selected percentages of variables for variable screening. The latest version added the variable screening function for both regression and classification problems.

Authors:Ye Tian [aut, cre] and Yang Feng [aut]

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RaSEn.pdf |RaSEn.html
RaSEn/json (API)
NEWS

# Install 'RaSEn' in R:
install.packages('RaSEn', repos = c('https://ytstat.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • colon - Colon data set.
  • rat - Affymetrix rat genome 230 2.0 array data set.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5 exports 1 stars 0.09 score 85 dependencies 6 scripts 537 downloads

Last updated 3 years agofrom:eba0e58f31. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-winWARNINGAug 20 2024
R-4.5-linuxWARNINGAug 20 2024
R-4.4-winWARNINGAug 20 2024
R-4.4-macWARNINGAug 20 2024
R-4.3-winWARNINGAug 20 2024
R-4.3-macWARNINGAug 20 2024

Exports:RaModelRaPlotRaRankRaScreenRase

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdoParalleldplyre1071fansifarverFNNforeachformatRfuturefuture.applygenericsggplot2glmnetglobalsgluegowergridExtragtablehardhatipredisobanditeratorsKernelKnnKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6randomForestrangerRColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

RaSEn demo

Rendered fromRaSEn-demo.Rmdusingknitr::rmarkdownon Aug 20 2024.

Last update: 2021-10-16
Started: 2020-06-12