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Comparative study on normalization procedures for cluster analysis of gene expression datasets.

, , , , , and . IJCNN, page 2792-2798. IEEE, (2008)

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Comparative study on proximity indices for cluster analysis of gene expression time series., , and . Journal of Intelligent and Fuzzy Systems, 13 (2-4): 133-142 (2002)A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods., , , and . IJCNN, page 643-648. IEEE, (2007)The diversity/accuracy dilemma: An empirical analysis in the context of heterogeneous ensembles., , and . IEEE Congress on Evolutionary Computation, page 939-946. IEEE, (2009)Analysis of complexity indices for classification problems: Cancer gene expression data., , , and . Neurocomputing, 75 (1): 33-42 (2012)Partitions selection strategy for set of clustering solutions., , , and . Neurocomputing, 73 (16-18): 2809-2819 (2010)Individual Clustering and Homogeneous Cluster Ensemble Approaches Applied to Gene Expression Data., , , , and . Australian Conference on Artificial Intelligence, volume 3809 of Lecture Notes in Computer Science, page 930-933. Springer, (2005)Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information., , and . BSB, volume 4643 of Lecture Notes in Computer Science, page 81-92. Springer, (2007)A Symbolic Approach to Gene Expression Time Series Analysis., , and . SBRN, page 25-30. IEEE Computer Society, (2002)How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity., , , , and . ACM Comput. Surv., 52 (5): 107:1-107:34 (2019)Extracting Symbolic Rules from Clustering of Gene Expression Data., , and . HIS, page 12. IEEE Computer Society, (2006)