Constrained Intelligent K-Means: Improving Results with Limited Previous Knowledge.

Authors:
Renato Cordeiro de Amorim
Affiliations:
-
Venue:
ADVCOMP '08 Proceedings of the 2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences
Year:
2008

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Abstract

It is here presented a new method for clustering that uses very limited amount of labeled data, employees two pairwise rules, namely must link and cannot link and a singlewise one, cannot cluster. It is demonstrated that the incorporation of these rules in the intelligent kmeans algorithm may increase the accuracy of results, this is proven with experiments where the real number of clusters in the data is unknown to the method.