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

de Amorim, Renato Cordeiro (2008) Constrained Intelligent K-Means : Improving Results with Limited Previous Knowledge. In: Procs of the Second Int Conf on Advanced Engineering Computing and Applications in Sciences, 2008 : ADVCOMP'08. Institute of Electrical and Electronics Engineers (IEEE), ESP, pp. 176-180. ISBN 978-0-7695-3369-8
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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 single wise one, cannot cluster. It is demonstrated that the incorporation of these rules in the intelligent k-means 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
Item Type Book Section
Date Deposited 15 May 2025 16:35
Last Modified 17 May 2025 05:15

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