scoresPlot: Function to Plot a Scores Plot

Description Usage Arguments Value Author(s)

View source: R/scoresPlot.R

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

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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 July 2, 2018, 1:03 a.m.