Self-Organizing Maps are cluster analysis, they are searching for groups (clusters) in the data, in such a way that objects belonging to the same cluster are quite similar, whereas objects in different clusters are dissimilar. They are also providing topological informations on the data ; the clusters are organised so that relative distances between groups on the grid reflect dissimilarities between groups in the data. Self-Organizing Maps have been used in several fields: voice recognition, image processing, process control, text analysis, genomic analysis... The package provide various tools for SOM: creation and learning, summary, print methods, groups extraction, plot methods, etc. Numerical and factorial variables are allowed in the data.
Package details |
|
---|---|
Author | David Gohel |
Maintainer | Stephen Kaluzny <spk@insightful.com> |
License | GNU GENERAL PUBLIC LICENSE Version 2 |
Version | 1.0.1 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.