Listar Producción Científica por autor "88409fbf-b48a-42fe-ba9c-3cfa24963178"
Mostrando ítems 1-20 de 32
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A case-study comparison of machine learning approaches for predicting student’s dropout from multiple online educational entities
Porras, José Manuel; Lara, Juan A.; Romero, Cristóbal; Ventura Soto, S. (MDPI, 2023)Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own ... -
Algoritmos Evolutivos para Descubrimiento de Reglas de Predicción en la Mejora de Sistemas Educativos Adaptativos basados en Web
Romero Morales, C.; Ventura Soto, S.; Castro Lozano, Carlos de; García, Enrique (Universidad de Castilla-La Mancha, Escuela Superior de Informática, 2005)Este artículo muestra la utilización de los algoritmos evolutivos para el descubrimiento de reglas de predicción que se utilizarán en la mejora de Cursos Hipermedia Adaptativos basados en Web. Se ha desarrollado una ... -
An Automatic Programming ACO-Based Algorithm for Classification Rule Mining
Olmo, J.L.; Luna, J.M.; Romero, J.R.; Ventura Soto, S. (2017-01-20)In this paper we present a novel algorithm, named GBAP, that jointly uses automatic programming with ant colony optimization for mining classification rules. GBAP is based on a context-free grammar that properly guides ... -
An intruder detection approach based on infrequent rating pattern mining
Luna, J.M.; Ramírez, A.; Romero, J.R.; Ventura Soto, S. (2014-02-26) -
Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers
Moyano, J.M.; Ventura Soto, S. (Elsevier, 2022)Multi-label classification has been used to solve a wide range of problems where each example in the dataset may be related either to one class (as in traditional classification problems) or to several class labels at the ... -
A Classification Module for Genetic Programming Algorithms in JCLEC
Cano, Alberto; Luna, J.M.; Zafra, Amelia; Ventura Soto, S. (MIT Press, 2014)JCLEC-Classi cation is a usable and extensible open source library for genetic program- ming classi cation algorithms. It houses implementations of rule-based methods for clas- si cation based on genetic programming, ... -
Classification Rule Mining with Iterated Greedy
Pedraza, Juan A.; García-Martínez, Carlos; Cano, Alberto; Ventura Soto, S. (2017-03-30)In the context of data mining, classi cation rule discovering is the task of designing accurate rule based systems that model the useful knowledge that di erentiate some data classes from others, and is present in large ... -
Course Recommendation based on Sequences: An Evolutionary Search of Emerging Sequential Patterns
Al‑Twijri, Mohammed Ibrahim; Luna, J.M.; Herrera, Francisco; Ventura Soto, S. (Springer, 2022)To provide a good study plan is key to avoid students’ failure. Academic advising based on student’s preferences, complexity of the semester, or even background knowledge is usually considered to reduce the dropout rate. ... -
Educational data mining and learning analytics: An updated survey
Romero Morales, C.; Ventura Soto, S. (Wiley, 2020)This survey is an updated and improved version of the previous one published in 2013 in this journal with the title “data mining in education”. It reviews in a comprehensible and very general way how Educational Data ... -
Evaluación distribuida transparente para algoritmos evolutivos en JCLEC
Cano, Alberto; Ventura Soto, S.; Ibáñez Pastor, Francisco (2017)La evaluaci ´on de los individuos en un algoritmo evolutivo constituye generalmente la etapa con un mayor coste computacional. Este hecho se acent ´ua en los problemas de miner´ıa de datos debido al cada vez mayor tama˜no ... -
Herramienta Autor para la Gestión de Tests Informatizados dentro del Sistema AHA!
Romero Morales, C.; Ventura Soto, S.; Hervás-Martínez, César; Rider, Isaac; Martín-Palomo, Santiago (Universidad de Castilla-La Mancha, Escuela Superior de Informática, 2006)En este artículo presentamos Test Editor, una herramienta autor para la construcción de test informatizados, tanto clásicos como adaptativos, a través del Web. Esta herramienta facilita el desarrollo y mantenimiento de ... -
Improving spiking neural network performance with auxiliary learning
Cachi, Paolo G.; Ventura Soto, S.; Cios, Krzysztof (MDPI, 2023)The use of back propagation through the time learning rule enabled the supervised training of deep spiking neural networks to process temporal neuromorphic data. However, their performance is still below non-spiking neural ... -
Improving the understanding of cancer in a descriptive way: An emerging pattern mining-based approach
Trasierras, Antonio Manuel; Luna, J.M.; Ventura Soto, S. (Wiley, 2021)This paper presents an approach based on emerging pattern mining to analyse cancer through genomic data. Unlike existing approaches, mainly focused on predictive purposes, the proposal aims to improve the understanding of ... -
Interactive multi-objective evolutionary optimization of software architectures
Ramírez, Aurora; Romero, José Raúl; Ventura Soto, S. (Elsevier, 2018)While working on a software specification, designers usually need to evaluate different architectural alternatives to be sure that quality criteria are met. Even when these quality aspects could be expressed in terms of ... -
JCLEC Meets WEKA!
Cano, Alberto; Luna, J.M.; Olmo Ortiz, Juan Luis; Ventura Soto, S. (2014-02-27)WEKA has recently become a very referenced DM tool. In spite of all the functionality it provides, it does not include any framework for the development of evolutionary algorithms. An evolutionary computation framework ... -
JCLEC-MO: A Java suite for solving many-objective optimization engineering problems
Ramírez, Aurora; Romero, José Raúl; García-Martínez, Carlos; Ventura Soto, S. (Elsevier, 2019)Although metaheuristics have been widely recognized as efficient techniques to solve real-world optimization problems, implementing them from scratch remains difficult for domain-specific experts without programming skills. ... -
LAIM discretization for multi-label data
Cano, Alberto; Luna, J.M.; Gibaja, Eva; Ventura Soto, S. (2017)Multi-label learning is a challenging task in data mining which has attracted growing attention in recent years. Despite the fact that many multi-label datasets have continuous features, general algorithms developed specially ... -
Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules
Pérez, Eduardo; Ventura Soto, S. (MDPI, 2021)Skin cancer is one of the most common types of cancers in the world, with melanoma being the most lethal form. Automatic melanoma diagnosis from skin images has recently gained attention within the machine learning community, ... -
Modeling and predicting students’ engagement behaviors using mixture Markov models
Maqsood, Rabia; Ceravolo, Paolo; Romero Morales, C.; Ventura Soto, S. (Springer, 2022)Students’ engagements reflect their level of involvement in an ongoing learning processwhich can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating ... -
Multi-Objective Genetic Programming for Feature Extraction and Data Visualization
Cano, Alberto; Ventura Soto, S.; Cios, Krzyztof J. (2017)Feature extraction transforms high dimensional data into a new subspace of lower dimensionalitywhile keeping the classification accuracy. Traditional algorithms do not consider the multi-objective nature of this task. ...