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Artículo
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 ...
Artículo
Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems
(Elsevier, 2013)
This paper combines feature selection methods with a two-stage evolutionary classifier based on product unit neural networks. The enhanced methodology has been tried out with four filters using 18 data sets that report ...
Artículo
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 ...
Artículo
Explaining deep learning models for ozone pollution prediction via embedded feature selection
(ScienceDirect, 2024)
Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is responsible for an estimated 1 to 1.2 million premature deaths yearly. Furthermore, O3 adversely affects ...
Artículo
Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection
(Elsevier, 2012)
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature ...
Artículo
MCFS: Min-cut-based feature-selection
(Elsevier, 2020)
In this paper, MCFS (Min-Cut-based feature-selection) is presented, which is a feature-selection algorithm based on the representation of the features in a dataset by means of a directed graph. The main contribution of our ...
Artículo
Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula
(Elsevier, 2013)
This work explores the use of different seismicity indicators as inputs for artificial neural networks. The combination of multiple indicators that have already been successfully used in different seismic zones by the ...
Artículo
A coral-reef approach to extract information from HTML tables
(Elsevier, 2022)
his article presents Coraline, which is a new table-understanding proposal. Its novelty lies in a coral-reef optimisation algorithm that addresses the problem of feature selection in synchrony with a clustering technique ...
Artículo
An adaptive methodology to discretize and select features
(SciEdu Press, 2013)
A lot of significant data describing the behavior or/and actions of systems can be collected in several domains. These data define some aspects, called features, that can be clustered in several classes. A qualitative or ...
Artículo
Incremental wrapper-based gene selection from microarray data for cancer classification
(Elsevier, 2006)
Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to ...