getBinaryRule: Getter set of binary rules (object PartitionWithLLR)

In VHDClassification: Discrimination/Classification in very high dimension with linear and quadratic rules.

Description

This function returns the binary rule for discrimination between data from class k and data from class l

Usage

getBinaryRule(object, k, l)

Arguments

object	An object of class PartitionWithLLR as returned by learnPartitionWithLLR
k	an existing label
l	an existing label

Value

A binary classification rule. Can either be an object of class LinearRule or an object of class QuadraticRule

Author(s)

Robin Girard

References

Fast rate of convergence in high dimensional linear discriminant analysis. R. Girard To appear in Journal of Nonparametric Statistics.\ Very high dimensional discriminant analysis with thresholding estimation. R. Girard. Submitted.

See Also

getLogLikeRatio

Examples

#try p=1000 , 5000, ...
p=100; n=20 ; mu=array(0,c(p,4)); mu[1:10,1]=2 ;mu[11:20,2]=2;C=array(c(1,20),p)
mu[21:30,3]=2
x=NULL; y=NULL;
for (k in 1:4){
    x=rbind(x,t(array(C^(1/2),c(p,n))*(matrix(rnorm(p*n),nrow=p,ncol=n))+array(mu[,k],c(p,n))));
    y=c(y,array(k,n))}
#Learning
LearnedLinearPartitionWithLLR=learnPartitionWithLLR(x,y,procedure='FDRThresh')
Rule=getBinaryRule(LearnedLinearPartitionWithLLR,1,2)
show(Rule)

VHDClassification documentation built on May 2, 2019, 2:38 a.m.