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gnu: Add r-nestedcv.
* gnu/packages/cran.scm (r-nestedcv): New variable. Change-Id: Id998b4192565c220f8d238963ef61217aed12bd3
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@ -10007,6 +10007,43 @@ (define-public r-n2r
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@acronym{NSW, Navigable Small World} graphs.")
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(license license:asl2.0)))
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(define-public r-nestedcv
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(package
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(name "r-nestedcv")
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(version "0.7.0")
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(source
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(origin
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(method url-fetch)
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(uri (cran-uri "nestedcv" version))
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(sha256
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(base32 "0jpg4il1niyizfq8kkk391x7anhp2s38mrfypa86skr08ca46zss"))))
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(properties `((upstream-name . "nestedcv")))
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(build-system r-build-system)
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(propagated-inputs (list r-caret
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r-data-table
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r-doparallel
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r-foreach
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r-ggplot2
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r-glmnet
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r-matrixstats
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r-matrixtests
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r-proc
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r-rfast
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r-rlang))
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(native-inputs (list r-knitr))
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(home-page "https://github.com/myles-lewis/nestedcv")
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(synopsis "Nested cross-validation with glmnet and caret")
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(description
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"This package implements nested cross-validation applied to the
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@code{glmnet} and @code{caret} packages. With glmnet this includes
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cross-validation of elastic net alpha parameter. A number of feature
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selection filter functions (t-test, Wilcoxon test, ANOVA, Pearson/Spearman
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correlation, random forest, ReliefF) for feature selection are provided and
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can be embedded within the outer loop of the nested CV. Nested CV can be also
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be performed with the @code{caret} package giving access to the large number
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of prediction methods available in @code{caret}.")
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(license license:expat)))
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(define-public r-network
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(package
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(name "r-network")
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