KIFall: Kendall Interaction Filter (KIF)

In KarimOualkacha/KIF: Kendall Interaction Filter for Variable Interaction Screening in Ultra High Dimensional Classification Problems

Description

an interaction screening procedure based on Kendall's Tau.

Usage

KIFall(Sample, y, ncor = 2, threshold)

Arguments

Sample	a numeric matrix containing the data with n rows (observations) and p columns (features).
y	the response variable. y must be a factor.
ncor	number of cores to use for code parallelization. Default is 2.
threshold	the number of relevant couples to select.

Details

KIF measure aims to select the relevant couples for the multi-class classification task. It is based on Kendall's Tau and ranges form 0 to 1. KIF is a model-free procedure, handles continuous, categorical or a mixture of continuous-categorical features, and is invariant under monotonic transformations. KIFall function computes KIF scores of all possible couples, then returns the "threshold" couples with highest scores.

Value

KIFall function returns the first "threshold" selected couples among all the selected couples.

Examples

## Not run: 
############### KIFall function ###############
library(mvtnorm)
set.seed(1)
n1 <- 100
n2 <- 100
n <- n1 +n2
p <- 500
sigma <- diag(p)
sigma[upper.tri(sigma)] <- 0.2
sigma[lower.tri(sigma)] <- 0.2
sigma1 <- sigma
sigma2 <- sigma
sigma1[1,2] <- 0.8
sigma1[2,1] <- 0.8
sigma1[3,4] <- 0.8
sigma1[4,3] <- 0.8
sigma2[3,4] <- -0.8
sigma2[4,3] <- -0.8
mean1 <- c(rep(0,p))
mean2 <- c(rep(0,p))
Sample <- rbind(rmvnorm(n1, mean1, sigma1), rmvnorm(n2, mean2, sigma2))
y <- c(rep(1,n1), rep(0,n2))
out <- KIFall(Sample, y, 4, 10)

## End(Not run)

KarimOualkacha/KIF documentation built on July 9, 2021, 8:55 a.m.