calcEuclideanDistance

Calculate the euclidean distance between a numeric matrix n * p and a numeric
vector of length p

internal

Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed.
The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).

Jeremy Gelb

geocmeans

Implementing Methods for Spatial Fuzzy Unsupervised
Classification

Philippe Apparicio

calcEuclideanDistance function

<dl><dt>m</dt>
<dd>A n * p matrix or dataframe with only numeric columns</dd>
<dt>v</dt>
<dd>A numeric vector of length p</dd></dl>

Arguments

Calculate the Euclidean distance — calcEuclideanDistance

<dl>

<dt>m</dt>
<dd>A n * p matrix or dataframe with only numeric columns</dd>


<dt>v</dt>
<dd>A numeric vector of length p</dd>

</dl>

calcEuclideanDistance: Calculate the Euclidean distance

Description

Usage

Value

Arguments

Examples