Qualitative identification of clinkers by fuzzy clustering

With the application of this code fuzzy classifier is identified by unsupervised fuzzy clustering. The most relevant trace elements were selected based on the obtained clusters by the modified version of Fisher interclass separability method. The classification of Portuguese and South African clinkers is used as an illustrative example. The results show that the proposed method is useful to identify compact classifiers that are able to determine the origin of the clinker; and the obtained classifier is easy to use and interpret for engineers and researchers, even when they are not familiar with the concept of fuzzy logic.

The algorithm is also described in:
J. Madár, J. Abonyi, F. Szeifert, Feedback linearizing control using hybrid neural networks identified by sensitivity approach, Engineering Applications of Artificial Intelligence, 343-351, 2005
(It is in the .zip file)

More MATLAB implementation on my website:
http://www.abonyilab.com/software-and-data