sanity_check

Check that the provided parameters are valid

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

sanity_check function

<dl><dt>dots</dt>
<dd>A list of parameters used</dd>
<dt>data</dt>
<dd>A numeric and complete dataframe</dd></dl>

Arguments

Parameter checking function — sanity_check

<dl>

<dt>dots</dt>
<dd>A list of parameters used</dd>


<dt>data</dt>
<dd>A numeric and complete dataframe</dd>

</dl>

sanity_check: Parameter checking function

Description

Usage

Value

Arguments

Examples