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Capítulo de Libro
Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection
(Springer, 2011)
This paper introduces a methodology that improves the accuracy of a two-stage algorithm in evolutionary product unit neural networks for classification tasks by means of feature selection. A couple of filters have been ...
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
On the evolutionary weighting of neighbours and features in the k-nearest neighbour rule
(Elsevier, 2019)
This paper presents an evolutionary method for modifying the behaviour of the k-Nearest-Neighbour clas sifier (kNN) called Simultaneous Weighting of Attributes and Neighbours (SWAN). Unlike other weighting methods, SWAN ...
Artículo
Selecting the best measures to discover quantitative association rules
(Elsevier, 2014)
The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly ...
Artículo
Obtaining optimal quality measures for quantitative association rules
(Elsevier, 2016)
There exist several works in the literature in which fitness functions based on a combination of weighted measures for the discovery of association rules have been proposed. Nevertheless, some differences in the measures ...
Artículo
EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion
(Elsevier, 2012)
Land use and land covers (LULC) maps are remote sensing products that are used to classify areas into different landscapes. Data fusion for remote sensing is becoming an important tool to improve classical approaches. ...
Ponencia
MOPNAR-BigData: un diseño MapReduce para la extracción de reglas de asociación cuantitativas en problemas de big data
(Asociación Española de Inteligencia Artificial, 2015-11)
El término big data se ha extendido rápidamente en el área de la minera de datos debido a que las grandes cantidades de datos que se generan hoy en da no pueden ser procesadas o analizadas por las técnicas tradicionales ...
Artículo
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
(Elsevier, 2017)
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes involved in breast cancer can be identified by immunohistochemistry. However, this method has ...
Ponencia
On the use of algorithms to discover motifs in DNA sequences
(IEEE, 2011)
Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging for specialists nowadays due to the difficulties they find to deeply understand gene regulatory ...
Ponencia
Análisis Big Data para la Respuesta a la Demanda en el Mercado Eléctrico
(Asociación Española para la Inteligencia Artificial (AEPIA), 2018)
El modelo de negocio tradicional de las compañías energéticas está cambiando los últimos años. La introducción de los contadores inteligentes ha conll evado un aumento exponencial del volumen de datos disponibles, y su ...