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Using Accuracy and Diversity to Select Classifiers to Build Ensembles.

, , , and . IJCNN, page 1310-1316. IEEE, (2006)

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On the performance of pairings of activation and loss functions in neural networks., and . IJCNN, page 326-333. IEEE, (2016)An Analysis of Meta-learning Techniques for Ranking Clustering Algorithms Applied to Artificial Data., , and . ICANN (1), volume 5768 of Lecture Notes in Computer Science, page 131-140. Springer, (2009)Comparative study on normalization procedures for cluster analysis of gene expression datasets., , , , , and . IJCNN, page 2792-2798. IEEE, (2008)Evolving both size and accuracy of RBF networks using Memetic Algorithm., , , and . IJCNN, page 1938-1944. IEEE, (2008)An evolutionary approach for the clustering data problem., , , and . IJCNN, page 1945-1950. IEEE, (2008)Empirical comparison of Dynamic Classifier Selection methods based on diversity and accuracy for building ensembles., , , and . IJCNN, page 1480-1487. IEEE, (2008)A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity., , , and . SBRN, page 36-41. IEEE Computer Society, (2006)Using Accuracy and Diversity to Select Classifiers to Build Ensembles., , , and . IJCNN, page 1310-1316. IEEE, (2006)Métodos de Machine Learning Aplicados no Cenário da Educaçáo a Distância Brasileira (Machine Learning Techniques Applied to the Brazilian Distance Education)., , and . SIIE, volume 2733 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Ranking and selecting clustering algorithms using a meta-learning approach., , , , , , and . IJCNN, page 3729-3735. IEEE, (2008)