Fuzzy Clustering of Ecological Data

Ordination and classification have always been important stages in ecological data analysis. This paper presents a clustering technique based on fuzzy sets to obtain both ordination and classification particularly well suited for ecological analyses. Three algorithms are presented to categorize data, classify new ones, and produce fuzzy dendrograms. Some examples demonstrate the algorithms’ capabilities to yield graded classification of data and show that this approach has more flexibility compared to classical methods.

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