# Nested Loop Cross Validation

## Documentation for package ‘nlcv’ version 0.3.6

- 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