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パッケージ: r-cran-unbalanced (2.0-2)

GNU R racing for unbalanced methods selection

A dataset is said to be unbalanced when the class of interest (minority class) is much rarer than normal behaviour (majority class). The cost of missing a minority class is typically much higher that missing a majority class. Most learning systems are not prepared to cope with unbalanced data and several techniques have been proposed. This package implements some of most well-known techniques and propose a racing algorithm to select adaptively the most appropriate strategy for a given unbalanced task.

その他の r-cran-unbalanced 関連パッケージ

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  • dep: r-api-4.0
    以下のパッケージによって提供される仮想パッケージです: r-base-core
  • dep: r-base-core (>= 4.1.1-2)
    GNU R core of statistical computation and graphics system
  • dep: r-cran-doparallel
    GNU R foreach parallel adaptor for the parallel package
  • dep: r-cran-fnn
    GNU R fast nearest neighbor search algorithms and applications
  • dep: r-cran-foreach
    GNU R foreach looping support
  • dep: r-cran-mlr
    Machine learning in GNU R
  • dep: r-cran-rann
    Fast Nearest Neighbour Search Using L2 Metric
  • sug: r-cran-randomforest
    GNU R package implementing the random forest classificator
  • sug: r-cran-rocr
    GNU R package to prepare and display ROC curves

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