Eucdist: Computes the Euclidean(square Euclidean) distance matrix

In qkerntool: Q-Kernel-Based and Conditionally Negative Definite Kernel-Based Machine Learning Tools

Description

Eucdist Computes the Euclidean(square Euclidean) distance matrix.

Arguments

x	(NxD) matrix (N samples, D features)
y	(MxD) matrix (M samples, D features)
sEuclidean	can be TRUE or FALSE, FALSE to Compute the Euclidean distance matrix.

Value

E - (MxN) Euclidean (square Euclidean) distances between vectors in x and y

Author(s)

Yusen Zhang
[e-mail]

Examples

###
data(iris)
testset <- sample(1:150,20)
x <- as.matrix(iris[-testset,-5])
y <- as.matrix(iris[testset,-5])

##
res0 <- Eucdist(x)
res1 <- Eucdist(x, x, sEuclidean = FALSE)
res2 <- Eucdist(x, y = NULL, sEuclidean = FALSE)
res3 <- Eucdist(x, x, sEuclidean = TRUE)
res4 <- Eucdist(x, y = NULL)
res5 <- Eucdist(x, sEuclidean = FALSE)

qkerntool documentation built on May 2, 2019, 6:11 a.m.