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Incremental wrapper-based gene selection from microarray data for cancer classification.

, , and . Pattern Recognit., 39 (12): 2383-2392 (2006)

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Apoyo a la Decisión en Ingeniería del Software (ADIS, 9ª edición)., , and . JISBD, page 426-426. (2009)Three Geometric Approaches for representing Decision Rules in a Supervised Learning System., , and . GECCO, page 771. Morgan Kaufmann, (1999)Prototype-based Mining of Numeric Data Streams., , and . SAC, page 480-484. ACM, (2003)Improvements in the Decision Making in Software Projects., , and . ICEIS (1), page 431-436. (2001)Obtención de Reglas de Clasificación Semicualitativas utilizando Algoritmos Genéticos y el C4.5., , and . IBERAMIA-SBIA 2000 Open Discussion Track, page 147-156. ICMC/USP, (2000)Projection-based measure for efficient feature selection., , and . J. Intell. Fuzzy Syst., 12 (3-4): 175-183 (2002)Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance., , , , , and . Artif. Intell. Medicine, (2020)Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production., , , and . Eur. J. Oper. Res., 185 (3): 1114-1127 (2008)An approach to validity indices for clustering techniques in Big Data., , , and . Prog. Artif. Intell., 7 (2): 81-94 (2018)A Tool to Obtain a Hierarchical Qualitative Rules form Quantitative Data., , and . IEA/AIE (Vol. 1), volume 1415 of Lecture Notes in Computer Science, page 336-346. Springer, (1998)