ComputeSimilarity: Compute Similarities

In rerf: Randomer Forest

Description

Computes pairwise similarities between observations. The similarity between two points is defined as the fraction of trees such that two points fall into the same leaf node.

Usage

ComputeSimilarity(X, forest, num.cores = 0L, Xtrain = NULL)

Arguments

X	an n sample by d feature matrix (preferable) or data frame which was used to train the provided forest.
forest	a forest trained using the rerf function, with COOB=TRUE.
num.cores	the number of cores to use while training. If num.cores=0 then 1 less than the number of cores reported by the OS are used. (num.cores=0)
Xtrain	an n by d numeric matrix (preferable) or data frame. This should be the same data matrix/frame used to train the forest, and is only required if RerF was called with rank.transform = TRUE. (Xtrain=NULL)

Value

similarity a normalized n by n matrix of pairwise similarities

Examples

library(rerf)
X <- as.matrix(iris[, 1:4])
Y <- iris[[5L]]
forest <- RerF(X, Y, num.cores = 1L)
sim.matrix <- ComputeSimilarity(X, forest, num.cores = 1L)

rerf documentation built on May 2, 2019, 8:16 a.m.