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).
scoresPlot(nlcvObj, tech, nfeat, plot = TRUE, barPlot = FALSE,
layout = TRUE, main = NULL, sub = NULL, ...)Object of class 'nlcv' as produced by the nlcv
function
string denoting the classification technique used; one of 'dlda', 'bagg', 'pam', 'rf', or 'svm'.
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)
logical. If FALSE, nothing is plotted.
Should a barplot be drawn (TRUE) or the alternative
MCREstimate-type scores plot (the default, FALSE).
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 title for the scores plot; if not supplied, 'Scores Plot' is used as a default
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
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).