Description Usage Arguments Value Author(s) See Also
plots for each classification technique and a given number of features used the mean misclassification rate (mcr) and its standard error across all runs of the nested loop crossvalidation.
1 
nlcvObj 
Object of class 'nlcv' as produced by the 
plot 
logical. If 
optimalDots 
Boolean indicating whether dots should be displayed on a panel below the graph to mark the optimal number of features for a given classification technique 
rescale 
if 
layout 
boolean indicating whether 
... 
Dots argument to pass additional graphical parameters (such as

An MCR plot is output to the device of choice. The dots represent the mean MCR across runs. The vertical lines below and above the dots represent the standard deviation of the MCR values across runs.
Below the plot coloured solid dots (one for each classification technique) indicate for which number of features a given technique reached its minimum MCR.
The function invisibly returns an object of class mcrPlot
which is a
list with components:
meanMcrMatrixmatrix with for each number of features (rows) and classification technique (columns) the mean of the MCR values across all runs of the nlcv procedure.
sdMcrMatrixmatrix with for each number of features (rows) and classification technique (columns) the sd of the MCR values across all runs of the nlcv procedure.
The summary
method for the mcrPlot
object returns a matrix
with for each classification technique, the optimal number of features as
well as the associated mean MCR and standard deviation of the MCR values.
Willem Talloen and Tobias Verbeke
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