nlcv (0.3.5)

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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) .

Maintainer: Laure Cougnaud
Author(s): Willem Talloen, Tobias Verbeke

License: GPL-3

Uses: e1071, ipred, kernlab, MASS, multtest, pamr, randomForest, RColorBrewer, ROCR, xtable, RUnit

Released almost 2 years ago.

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