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How Many Clusters: A Validation Index for Arbitrary-Shaped Clusters
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Ariel E. Baya,Pablo M. Granitto
Issue Date:March 2013
pp. 401-414
Clustering validation indexes are intended to assess the goodness of clustering results. Many methods used to estimate the number of clusters rely on a validation index as a key element to find the correct answer. This paper presents a new validation index...
 
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems
Found in: Hybrid Intelligent Systems, International Conference on
By HernĂ¡n Ahumada, Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto, Alejandro Ceccatto
Issue Date:September 2008
pp. 386-391
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical applications. In this work we introduce the Recursive Partitioning of the Majori...
 
How Many Clusters: A Validation Index for Arbitrary-Shaped Clusters
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Ariel E. Baya, Pablo M. Granitto
Issue Date:March 2013
pp. 401-414
Clustering validation indexes are intended to assess the goodness of clustering results. Many methods used to estimate the number of clusters rely on a validation index as a key element to find the correct answer. This paper presents a new validation index...
     
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