Visualize Separability of different classes
Description
Given two variables, the methods trains a classifier
(argument classifier
) based on these two variables
and plots the resulting class regions, learning and test
observations in the plane.
Appropriate variables are usually found by GeneSelection
.
For S4 method information, s. Planarplotmethods
.
Usage
1  Planarplot(X, y, f, learnind, predind, classifier, gridsize = 100, ...)

Arguments
X 
Gene expression data. Can be one of the following:

y 
Class labels. Can be one of the following:

f 
A twosided formula, if 
learnind 
An index vector specifying the observations that
belong to the learning set. May be 
predind 
A vector containing exactly two indices that denote the two variables used for classification. 
classifier 
Name of function ending with 
gridsize 
The gridsize used for twodimensional plotting. For both variables specified in 
... 
Further argument passed to 
Value
No return.
Author(s)
Martin Slawski ms@cs.unisb.de
AnneLaure Boulesteix boulesteix@ibe.med.unimuenchen.de.
Idea is from the MLInterfaces
package, contributed
by Jess Mar, Robert Gentleman and Vince Carey.
See Also
GeneSelection
,
compBoostCMA
, dldaCMA
, ElasticNetCMA
,
fdaCMA
, flexdaCMA
, gbmCMA
,
knnCMA
, ldaCMA
, LassoCMA
,
nnetCMA
, pknnCMA
, plrCMA
,
pls_ldaCMA
, pls_lrCMA
, pls_rfCMA
,
pnnCMA
, qdaCMA
, rfCMA
,
scdaCMA
, shrinkldaCMA
, svmCMA
Examples
1 2 3 4 5 6 7 8 9 