# R/euclideanDistance.R In LearnClust: Learning Hierarchical Clustering Algorithms

#### Documented in edistance

```#' @title To calculate the Euclidean distance.
#' @description To calculate the Euclidean distance of two clusters.
#' @param x is a numeric vector or a matrix. It represents the values of a cluster.
#' @param y is a numeric vector or a matrix. It represents the values of a cluster.
#' @details This function is part of the hierarchical clusterization method. The function calculates the
#' Euclidean distance value from \code{x} and \code{y}.
#' @author Roberto Alcántara \email{roberto.alcantara@@edu.uah.es}
#' @author Universidad de Alcalá de Henares
#' @return Euclidean distance value.
#' @examples
#'
#' x <- c(1,2)
#' y <- c(1,3)
#'
#' cluster1 <- matrix(x,ncol=2)
#' cluster2 <- matrix(y,ncol=2)
#'
#' edistance(x,y)
#'
#' edistance(cluster1,cluster2)
#'
#' @export

edistance <- function(x,y){
sqrt(((y[1] - x[1])^2) + ((y[2] - x[2])^2))
}
```

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LearnClust documentation built on Nov. 30, 2020, 1:09 a.m.