scoresPlot: Function to Plot a Scores Plot

In nlcv: Nested Loop Cross Validation

Description

Function to plot, for a given nested loop cross-validation object, a given classification technique and a given number of features used for the classification, the scores plot. This plot diplays the proportion of correctly-classified per sample across all runs of the nested loop cross-validation. The class membership of the samples is displayed using a colored strip (with legend below the plot).

Usage

scoresPlot(nlcvObj, tech, nfeat, plot = TRUE, barPlot = FALSE,
  layout = TRUE, main = NULL, sub = NULL, ...)

Arguments

nlcvObj	Object of class 'nlcv' as produced by the nlcv function
tech	string denoting the classification technique used; one of 'dlda', 'bagg', 'pam', 'rf', or 'svm'.
nfeat	integer giving the number of features; this number should be part of the initial set of number of features that was specified during the nested loop cross-validation (nFeatures argument of the nlcv function)
plot	logical. If FALSE, nothing is plotted.
barPlot	Should a barplot be drawn (TRUE) or the alternative MCREstimate-type scores plot (the default, FALSE).
layout	boolean indicating whether mcrPlot should prespecify a layout for a single plot (default, TRUE) or whetherl the user takes care of the layout (FALSE)
main	Main title for the scores plot; if not supplied, 'Scores Plot' is used as a default
sub	Subtitle for the scores plot; if not supplied, the classification technique and the chosen number of features are displayed
...	Additional graphical parameters to pass to the plot function

Value

A scores plot is displayed (for the device specified).

The function invisibly returns a named vector containing (for each sample) the proportion of times the sample was correctly classified (for a given technique and a given number of features used).

Author(s)

Willem Talloen and Tobias Verbeke

nlcv documentation built on May 2, 2019, 7:28 a.m.