plot,cloutput-method: Probability plot
In CMA: Synthesis of microarray-based classification

Description Arguments Value Note Author(s) References See Also

A popular way of visualizing the output of classifier is to plot, separately for each class, the predicted probability of each predicted observations for the respective class. For this purpose, the plot area is divided into K parts, where K is the number of classes. Predicted observations are assigned, according to their true class, to one of those parts. Then, for each part and each predicted observation, the predicted probabilities are plotted, displayed by coloured dots, where each colour corresponds to one class.

`x`	An object of class `cloutput` whose slot `probmatrix` does not contain any missing value, i.e. probability estimations are provided by the classifier.
`main`	A title for the plot (character).

No return.

The plot usually only makes sense if a sufficiently large numbers of observations has been classified. This is usually achieved by running the classifier on several learningsets with the method classification. The output can then be processed via join to obtain an object of class cloutput to which this method can be applied.

Martin Slawski ms@cs.uni-sb.de

Anne-Laure Boulesteix boulesteix@ibe.med.uni-muenchen.de

Slawski, M. Daumer, M. Boulesteix, A.-L. (2008) CMA - A comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinformatics 9: 439

cloutput

CMA documentation built on Nov. 8, 2020, 5:02 p.m.