# clusterDistance.details: To explain how to calculate the distance between clusters. In LearnClust: Learning Hierarchical Clustering Algorithms

## Description

To explain how to calculate the distance between clusters depending on the approach and distance type.

## Usage

 `1` ```clusterDistance.details(cluster1, cluster2, approach, distance) ```

## Arguments

 `cluster1` is a matrix `cluster2` is a matrix `approach` is a string. Type of function to apply. `distance` is a string. Type of distance to use.

## Details

This function is part of the hierarchical clusterization method. The function explains how to calculate the final distance between `cluster1` and `cluster2` applying the approach definition, using the distance type given.

`approach` indicates the algorithm used to get the value. `distance` indicates the distance used to get the value. Possible values: `'MAX'`, `'MIN'`, `'AVG'`.

## Value

Distance between clusters. Explanation.

## Author(s)

Roberto Alcántara roberto.alcantara@edu.uah.es

 ```1 2 3 4 5 6``` ```cluster1 <- matrix(c(1,2),ncol=2) cluster2 <- matrix(c(1,4),ncol=2) clusterDistance.details(cluster1,cluster2,'AVG','MAN') clusterDistance.details(cluster1,cluster2,'MAX','OCT') ```