diss_euclidean: Euclidean dissimilarity method constructor

In resemble: Similarity Retrieval and Local Learning for Spectral Chemometrics

Euclidean dissimilarity method constructor

Description

Creates a configuration object for computing Euclidean dissimilarity. Pass the result to dissimilarity() to compute the dissimilarity matrix.

The scaled Euclidean dissimilarity between two observations x_i and x_j is:

d(x_i, x_j) = \sqrt{\frac{1}{p} \sum_{k=1}^{p}(x_{i,k} - x_{j,k})^2}

where p is the number of variables. Results are equivalent to stats::dist() but scaled by 1/p.

Usage

diss_euclidean(center = TRUE, scale = FALSE)

Arguments

center	Logical. Center the data before computing distances? Applied jointly to Xr and Xu if both are provided. Default TRUE.
scale	Logical. Scale the data before computing distances? Applied jointly to Xr and Xu if both are provided. Default FALSE.

Value

An object of class c("diss_euclidean", "diss_method").

Author(s)

Leonardo Ramirez-Lopez

See Also

dissimilarity, diss_mahalanobis, diss_cosine

Examples

m <- diss_euclidean()
m <- diss_euclidean(center = FALSE, scale = TRUE)

resemble documentation built on April 21, 2026, 1:07 a.m.