Supervised - Parallelepiped, minimum distance, maximum likelihood, and Fisher supervised classifiers.
- Neural network classifiers including multi-layer perceptron, self-organizing map, and fuzzy ARTMAP.
Unsupervised - Histogram peak cluster analysis, k-means, and iterative self-organizing cluster analysis for unsupervised classification.
- Dempster-Shafer maximum set basic probability classifier.
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| IDRISI has incomparable classification tools. In particular, our hard classifiers include the traditional maximum likelihood, minimum distance and parallelepiped classifiers, as well as linear discriminate analysis, k-nearest neighbor, cluster and k-means unsupervised classifiers. Machine learning classifiers consist of three neural network classifiers--multi-layer perceptron, self-organizing map, and fuzzy art map. IDRISI also includes a decision tree classifier.
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