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nlcv
View on CRAN: Click
here
Download and install nlcv package within the R console
Install from CRAN:
install.packages("nlcv")
Install from Github:
library("remotes")
install_github("cran/nlcv") Install by package version:
library("remotes")
install_version("nlcv", "0.3.6") Attach the package and use:
library("nlcv")
Maintained by
Laure Cougnaud
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-10-19
Latest Update: 2025-05-06
Description:
Nested loop cross validation for classification purposes for misclassification error rate estimation.
The package supports several methodologies for feature selection: random forest, Student t-test, limma,
and provides an interface to the following classification methods in the 'MLInterfaces' package: linear,
quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized
linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of
the classifier are included: plot of the ranks of the features, scores plot for a specific
classification algorithm and number of features, misclassification rate
for the different number of features and classification algorithms tested and ROC plot.
For further details about the methodology, please check:
Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004)
.
How to cite:
Laure Cougnaud (2017). nlcv: Nested Loop Cross Validation. R package version 0.3.6, https://cran.r-project.org/web/packages/nlcv. Accessed 05 Mar. 2026.
Previous versions and publish date:
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Complete documentation for nlcv
Functions, R codes and Examples using
the nlcv R package
Some associated functions: compareOrig . confusionMatrix.nlcv . inTrainingSample . limmaTwoGroups . mcrPlot . nlcv . nlcvRF_R . nlcvRF_SHS . nlcvRF_SS . nlcvRF_WHS . nlcvRF_WS . nlcvTT_R . nlcvTT_SHS . nlcvTT_SS . nlcvTT_WHS . nlcvTT_WS . nldaI . pamrI . pamrIconverter . pamrML . pamrTrain . predict.pamrML . print.nlcvConfusionMatrix . print.pamrML . print.summary.mcrPlot . rankDistributionPlot . rocPlot . scoresPlot . summary.mcrPlot . topTable-methods . xtable.confusionMatrix . xtable.summary.mcrPlot .
Some associated R codes: classify_bioc_2.3.R . compareOrig.R . confusionMatrix.R . data.R . inTrainingSample.R . limma.R . mcrPlot.R . nlcv.R . nldaI.R . pamrI.R . rankDistributionPlot.R . rocPlot.R . scoresPlot.R . topTable.R . xtable.confusionMatrix.R . xtable.summary.mcrPlot.R . zzz.R . Full nlcv package functions and examples
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