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Artículo
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Filter‑based feature selection in the context of evolutionary neural networks in supervised machine learning
(Springer, 2020)
This paper presents a workbench to get simple neural classifcation models based on product evolutionary networks via a prior data preparation at attribute level by means of flter-based feature selection. Therefore, the ...
Capítulo de Libro
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Fast Feature Ranking Algorithm
(2003)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. The algorithm has ...
Artículo
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Presentación: Minería de Datos
(Asociación Española para la Inteligencia Artificial, 2006)
La Minería de Datos ha experimentado en los últimos años una notable explosión de interés tanto en ámbitos académicos como industriales. Se trata de un área interdisciplinar fuertemente relacionada con el aprendizaje ...
Capítulo de Libro
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SOAP: Efficient Feature Selection of Numeric Attributes
(2002)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. Depending on the ...
Ponencia
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Best Agglomerative Ranked Subset for Feature Selection
(2008-09)
The enormous increase of the size in databases makes finding an optimal subset of features extremely difficult. In this paper, a new feature selection method is proposed that will allow any subset evaluator -including the ...
Capítulo de Libro
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Evolutionary q-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection
(2010)
This paper proposes a Radial Basis Function Neural Network (RBFNN) which reproduces different Radial Basis Functions (RBFs) by means of a real parameter q, named q-Gaussian RBFNN. The architecture, weights and node topology ...
Capítulo de Libro
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Analysis of Feature Rankings for Classification
(2005)
Different ways of contrast generated rankings by feature selection algorithms are presented in this paper, showing several possible interpretations, depending on the given approach to each study. We begin from the premise ...
Artículo
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Semi-wrapper feature subset selector for feed-forward neural networks: Applications to binary and multi-class classification problems
(ScienceDirect, 2019-08-11)
This paper explores widely the data preparation stage within the process of knowledge discovery and data mining via feature subset selection in the context of two very well-known neural models: radial basis function neural ...
Capítulo de Libro
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Efficient Incremental-Ranked Feature Selection in Massive Data
(Chapman and Hall/CRC, 2007)
Ponencia
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Searching for Rules to find Defective Modules in Unbalanced Data Sets
(IEEE Xplore, 2009-05)
The characterisation of defective modules in software engineering remains a challenge. In this work, we use data mining techniques to search for rules that indicate modules with a high probability of being defective. Using ...