Nested Loop Cross Validation

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Documentation for package ‘nlcv’ version 0.3.5

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

compareOrig	function to compare the original matrix of correct classes to each component of the output object for a certain classifier
confusionMatrix.nlcv	compute a confusion matrix for the optimal number of features for a given technique used in the nested loop cross validation
inTrainingSample	Function to define a learning sample based on balanced sampling
limmaTwoGroups	Wrapper around limma for the comparison of two groups
mcrPlot	Misclassification Rate Plot
nlcv	Nested Loop Cross-Validation
nlcvRF_R	nlcv results on random data with random forest feature selection
nlcvRF_SHS	nlcv results on strong hetero signal data with random forest feature selection
nlcvRF_SS	nlcv results on strong signal data a with random forest feature selection
nlcvRF_WHS	nlcv results on weak signal data with random forest feature selection
nlcvRF_WS	nlcv results on weak hetero signal data with random forest feature selection
nlcvTT_R	nlcv results on random data with t-test feature selection
nlcvTT_SHS	nlcv results on strong hetero signal data with t-test feature selection
nlcvTT_SS	nlcv results on strong signal data a with t-test feature selection
nlcvTT_WHS	nlcv results on weak signal data with t-test feature selection
nlcvTT_WS	nlcv results on weak hetero signal data with t-test feature selection
nldaI	new MLInterfaces schema for lda from MASS
pamrI	Instance of a learnerSchema for pamr models
pamrIconverter	convert from 'pamrML' to 'classifierOutput'
pamrML	Wrapper function around the pamr.* functions
pamrTrain	Function providing a formula interface to pamr.train
predict.pamrML	predict 'pamrML' object
print.nlcvConfusionMatrix	print object 'nlcvConfusionMatrix'
print.pamrML	print 'pamrML' object
print.summary.mcrPlot	'print' function for 'summary.mcrPlot' object
rankDistributionPlot	Plot the Distribution of Ranks of Features Across nlcv Runs
rocPlot	Produce a ROC plot for a classification model belonging to a given technique and with a given number of features.
scoresPlot	Function to Plot a Scores Plot
summary.mcrPlot	'summary' function for 'mcrPlot' object
topTable	Methods for topTable
topTable-method	Methods for topTable
topTable-methods	Methods for topTable
xtable.confusionMatrix	xtable method for confusionMatrix objects
xtable.summary.mcrPlot	xtable method for summary.mcrPlot objects