nlcv: Nested Loop Cross Validation

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) <doi:10.2202/1544-6115.1078>.

Version: 0.3.5
Depends: R (≥ 2.10), a4Core, MLInterfaces (≥ 1.22.0), xtable
Imports: limma, MASS, methods, graphics, Biobase, multtest, RColorBrewer, pamr, randomForest, ROCR, ipred, e1071, kernlab
Suggests: RUnit, ALL
Published: 2018-06-29
DOI: 10.32614/CRAN.package.nlcv
Author: Willem Talloen, Tobias Verbeke
Maintainer: Laure Cougnaud <laure.cougnaud at>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: nlcv results


Reference manual: nlcv.pdf
Vignettes: nlcv


Package source: nlcv_0.3.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): nlcv_0.3.5.tgz, r-oldrel (arm64): nlcv_0.3.5.tgz, r-release (x86_64): nlcv_0.3.5.tgz, r-oldrel (x86_64): nlcv_0.3.5.tgz
Old sources: nlcv archive

Reverse dependencies:

Reverse suggests: a4, a4Base


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