pcd_inhull_classifier: The PCD classifier based on the cover of the two (or more)...

In Artur-man/PCDSL: Proximity Catch Digraphs: Statistical Learning

The PCD classifier based on the cover of the two (or more) classes wherein the cover of the target class is restricted to the inside of the convex hull of the non-target class.

Description

The PCD classifier based on the cover of the two (or more) classes wherein the cover of the target class is restricted to the inside of the convex hull of the non-target class.

Usage

pcd_inhull_classifier(data, classes, map = "pe", param = 1)

Arguments

data	An n-by-d matrix of the training data set.
classes	A vector of length n indicating the labels of the classes.
map	The Proximity Map associated with the classifier. "pe" for the Proportional-edge proximity maps. and "cs" for the Central-similarity proximity maps.
param	The value of the parameter associated with the proximity map.

Value

A proximity catch digraph (PCD)

Examples

# input parameters
ntest <- 100     # test data size for each class
nx <- 300        # training data size of x class (majority)
r <- 0.1         # Imbalance Ratio
de <- 0.5        # delta, the overlapping parameter
dimx <- 2        # number of dimensions

# training the classifier
set.seed(1)
x0 <- matrix(runif(dimx*nx,0,1),nrow=nx)
x1 <- matrix(runif(dimx*nx*r,de,1+de),nrow=nx*r)
x <- rbind(x0,x1)
classes <- rep(1:2,c(nx,nx*r))
graph_pcd <- pcd_inhull_classifier(x,classes,map="pe",param = 1)

Artur-man/PCDSL documentation built on Feb. 24, 2024, 11:15 p.m.