NameMartínez Ballesteros, María del Mar
DepartmentLenguajes y Sistemas Informáticos
Knowledge areaLenguajes y Sistemas Informáticos
Professional categoryProfesora Titular de Universidad
E-mailRequest
           
  • No. publications

    32

  • No. visits

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    4231


 

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Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance

Macías García, Laura; Martínez Ballesteros, María del Mar; Luna Romera, José María; García Heredia, José Manuel; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (Elsevier, 2020-01-01)
Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the ...
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Analysis of the evolution of the Spanish labour market through unsupervised learning

Luna Romera, José María; Núñez Hernández, Fernando; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal; Ibáñez, Carlos Usabiaga (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01)
Unemployment in Spain is one of the biggest concerns of its inhabitants. Its unemployment rate is the second highest in ...
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External clustering validity index based on chi-squared statistical test

Luna Romera, José María; Martínez Ballesteros, María del Mar; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (Elsevier, 2019-01-01)
Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so ...
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An approach to validity indices for clustering techniques in Big Data

Luna Romera, José María; García Gutiérrez, Jorge; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (Springer, 2018-01-01)
Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some ...
Presentation
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Aproximación al índice externo de validación de clustering basado en chi cuadrado

Luna Romera, José María; García Gutiérrez, Jorge; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (Asociación Española para la Inteligencia Artificial (AEPIA), 2018-01-01)
El clustering es una de las técnicas más utilizadas en minería de datos. Tiene como objetivo principal agrupar datos en ...
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MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems

Martín, D.; Martínez Ballesteros, María del Mar; García Gil, D.; Alcalá Fernández, J.; Herrera, F.; Riquelme Santos, José Cristóbal (Elsevier, 2018-01-01)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. ...
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A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation

Macías García, Laura; Luna Romera, José María; García Gutiérrez, Jorge; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal; González Cámpora, Ricardo (Elsevier, 2017-01-01)
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes ...
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Predicción de módulos defectuosos como un problema de optimización multiobjetivo

Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal; Ruiz, R.; Rodríguez, D. (Asociación de Ingeniería del Software y Tecnologías de Desarrollo de Software (SISTEDES), 2017-01-01)
La dificultad de aplicar técnicas de análisis de datos al problema de la calidad del software radica principalmente en dos ...
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Applications of Computational Intelligence in Time Series

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Reyes, Jorge; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (Hindawi, 2017-01-01)
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Machine learning techniques to discover genes with potential prognosis role in Alzheimer’s disease using different biological sources

Martínez Ballesteros, María del Mar; García Heredia, José Manuel; Nepomuceno Chamorro, Isabel de los Ángeles; Riquelme Santos, José Cristóbal (Elsevier, 2017-01-01)
Alzheimer’s disease is a complex progressive neurodegenerative brain disorder, being its prevalence ex pected to rise over ...
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Obtaining optimal quality measures for quantitative association rules

Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Elsevier, 2016-01-01)
There exist several works in the literature in which fitness functions based on a combination of weighted measures for the ...
Presentation
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An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark

Luna Romera, José María; Martínez Ballesteros, María del Mar; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (Springer, 2016-01-01)
K-Means and Bisecting K-Means clustering algorithms need the optimal number into which the dataset may be divided. Spark ...
Presentation
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Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules

Sánchez Medina, Alejandro; Gil Pichardo, Alberto; García Heredia, José Manuel; Martínez Ballesteros, María del Mar (Springer, 2016-01-01)
This work proposes a methodology to identify genes highly related with cancer. In particular, a multi-objective evolutionary ...
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A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting

Talavera Llames, Ricardo L.; Pérez Chacón, Rubén; Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco (Springer, 2016-01-01)
A forecasting algorithm for big data time series is presented in this work. A nearest neighbours-based strategy is adopted ...
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Improving a multi-objective evolutionary algorithm to discover quantitative association rules

Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Springer, 2015-01-01)
This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association ...
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Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

Martínez Ballesteros, María del Mar; Bacardit, Jaume; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (iOS Press, 2015-01-01)
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes ...
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Discovering gene association networks by multi-objective evolutionary quantitative association rules

Martínez Ballesteros, María del Mar; Nepomuceno Chamorro, Isabel de los Ángeles; Riquelme Santos, José Cristóbal (Elsevier, 2014-01-01)
In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the ...
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Selecting the best measures to discover quantitative association rules

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Elsevier, 2014-01-01)
The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate ...
Chapter of Book
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A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2013-01-01)
There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of ...
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An evolutionary algorithm to discover quantitative association rules in multidimensional time series

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is ...
Chapter of Book
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Analysis of Measures of Quantitative Association Rules

Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
This paper presents the analysis of relationships among different interestingness measures of quality of association rules ...
PhD Thesis
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Evolutionary Algorithms to Discover Quantitative Association Rules

Riquelme Santos, José Cristóbal; Troncoso Lora, Alicia; Martínez Ballesteros, María del Mar (2011-01-01)
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Extensiones para el Ciclo de Mejora Continua en la enseñanza e investigación de Ingeniería Informática

Álvarez de la Concepción, Miguel Ángel; Jiménez Ramírez, Andrés; Martínez Ballesteros, María del Mar; Martínez Gasca, Rafael; Parody Núñez, María Luisa; Soria Morillo, Luis Miguel (2011-01-01)
Este trabajo expone cómo añadiendo aspectos relacionados con la vigilancia tecnológica, las técnicas creativas aplicadas ...
Chapter of Book
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Inferring Gene-Gene Associations from Quantitative Association Rules

Martínez Ballesteros, María del Mar; Nepomuceno Chamorro, Isabel de los Ángeles; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...
Presentation
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On the use of algorithms to discover motifs in DNA sequences

Rubio Escudero, Cristina; Martínez Álvarez, Francisco; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging ...
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Evolutionary association rules for total ozone content modeling from satellite observations

Martínez Ballesteros, María del Mar; Salcedo Sanz, S.; Riquelme Santos, José Cristóbal; Casanova Mateo, C.; Camacho, J. L. (Elsevier, 2011-01-01)
In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association ...
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Mining Quantitative Association Rules in Microarray Data Using Evolutive Algorithms

Martínez Ballesteros, María del Mar; Rubio Escudero, Cristina; Riquelme Santos, José Cristóbal; Martínez Álvarez, Francisco (SciTePress, 2011-01-01)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...
Presentation
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Cis-cop: Multiobjective identification of cis-regulatory modules based on constrains

Romero Zaliz, Rocío; Martínez Ballesteros, María del Mar; Zwir, Igor; Val, Coral del (Universidad de Huelva, 2010-01-01)
Gene expression regulation is an intricate, dynamic phenomenon essential for all biolog ical functions. The necessary ...
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Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution

Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (IOS Press, 2010-01-01)
This research presents the mining of quantitative association rules based on evolutionary computation techniques. First, ...
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EVFUZZYSYSTEM: evolución de sistemas difusos para problemas de regresión multi-dimensionales

Martínez Ballesteros, María del Mar; Rivas, Víctor M. (Universidad de Huelva, 2010-01-01)
Este trabajo presenta EvFuzzySystem, un método evolutivo que permite el diseño com pleto de sistemas de lógica difusa, ...
Chapter of Book
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Quantitative Association Rules Applied to Climatological Time Series Forecasting

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (2009-01-01)
This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships ...
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Descubriendo Reglas de Asociación Numéricas entre Series Temporales

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Universidad de Sevilla, 2009-01-01)
Este trabajo presenta el descubrimiento de reglas de asociación basadas en técnicas evolutivas para obtener relaciones ...