Exploració per autor "González Navarro, Félix Fernando"
Ara es mostren els items 12-16 de 16
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Machine learning methods for classifying normal vs. tumorous tissue with spectral data
González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2009)
Text en actes de congrés
Accés obertMachine learning is a powerful paradigm within which to analyze 1H-MRS spectral data for the automated classi¯cation of tumor pathologies aimed to facilitate clinical diagnosis. The high dimensionality of the involved ... -
Parsimonious selection of useful genes in microarray gene expression data
González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Springer, 2011)
Capítol de llibre
Accés obertMachine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number ... -
TFS: a thermodynamical search algorithm for feature subset selection
González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Thomson Editores Spain, 2007)
Text en actes de congrés
Accés obertThis work tackles the problem of selecting a subset of features in an inductive learning setting, by introducing a novel Thermodynamic Feature Selection algorithm (TFS). Given a suitable objective function, the algorithm ... -
Un algoritmo para el cálculo de la relevancia entrópica multivariada y su uso en la selección de variables
González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Thomson Editores Spain, 2007)
Text en actes de congrés
Accés obertLa reducción de la dimensionalidad mediante la selección de variables es uno de los pasos fundamentales del preprocesado de datos, como fase previa al análisis de información y descubrimiento de conocimiento. De entre los ... -
Using machine learning techniques to explore H-1-MRS data of brain tumors
González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (IEEE Computer Society Publications, 2009)
Text en actes de congrés
Accés obertMachine learning is a powerful paradigm to analyze Proton Magnetic Resonance Spectroscopy (1H-MRS) spectral data for the classification of brain tumor pathologies. An important characteristic of this task is the high ...