Publicaciones en las que colabora con Julián Luengo Martín (35)

2023

  1. TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning

    Neurocomputing, Vol. 517, pp. 223-228

2022

  1. 3SHACC: Three stages hybrid agglomerative constrained clustering

    Neurocomputing, Vol. 490, pp. 441-461

2021

  1. Enhancing instance-level constrained clustering through differential evolution

    Applied Soft Computing, Vol. 108

  2. ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism

    Swarm and Evolutionary Computation, Vol. 66

  3. Synthetic Sample Generation for Label Distribution Learning

    Information Sciences, Vol. 544, pp. 197-213

2020

  1. Agglomerative Constrained Clustering Through Similarity and Distance Recalculation

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. DILS: Constrained clustering through dual iterative local search

    Computers and Operations Research, Vol. 121

  3. Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism

    GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference

  4. Similarity-based and Iterative Label Noise Filters for Monotonic Classification

    Proceedings of the Annual Hawaii International Conference on System Sciences

2019

  1. Label noise filtering techniques to improve monotonic classification

    Neurocomputing, Vol. 353, pp. 83-95

  2. Smartdata: Data preprocessing to achieve smart data in R

    Neurocomputing, Vol. 360, pp. 1-13

2017

  1. KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

    International Journal of Computational Intelligence Systems, Vol. 10, Núm. 1, pp. 1238-1249

2016

  1. From Big Data to Smart Data with the K-Nearest Neighbours Algorithm

    Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016

  2. The influence of noise on the evolutionary fuzzy systems for subgroup discovery

    Soft Computing, Vol. 20, Núm. 11, pp. 4313-4330

  3. Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

    Knowledge-Based Systems, Vol. 98, pp. 1-29

2015

  1. A data mining software package including data preparation and reduction: Keel

    Intelligent Systems Reference Library, Vol. 72, pp. 285-313

  2. A first approach in the class noise filtering approaches for fuzzy subgroup discovery

    Advances in Intelligent Systems and Computing

  3. Data Preprocessing in Data Mining

    Intelligent Systems Reference Library, Vol. 72

  4. Data preparation basic models

    Intelligent Systems Reference Library, Vol. 72, pp. 39-57

  5. Data reduction

    Intelligent Systems Reference Library, Vol. 72, pp. 147-162