no code implementations • 9 Feb 2024 • Xiaoxuan Zhang, Quan Pan, Salvador García
MSADGN can extract domain-invariant and domain-specific features from one labeled source domain and multiple unlabeled source domains, and then generalize these features to an arbitrary unseen target domain for real-time prediction of sea\textendash land clutter.
no code implementations • 26 Oct 2023 • Rakshitha Godahewa, Christoph Bergmeir, Zeynep Erkin Baz, Chengjun Zhu, Zhangdi Song, Salvador García, Dario Benavides
To fill this gap, we propose a simple linear-interpolation-based approach that is applicable to stabilise the forecasts provided by any base model vertically and horizontally.
no code implementations • 28 Feb 2023 • Germán González-Almagro, Daniel Peralta, Eli de Poorter, José-Ramón Cano, Salvador García
To remedy this, this study presents in-detail the background of constrained clustering and provides a novel ranked taxonomy of the types of constraints that can be used in constrained clustering.
no code implementations • 25 Feb 2023 • Germán González-Almagro, Juan Luis Suárez, Pablo Sánchez-Bermejo, José-Ramón Cano, Salvador García
This study addresses the problem of performing clustering in the presence of two types of background knowledge: pairwise constraints and monotonicity constraints.
no code implementations • 21 Apr 2022 • Alejandro Rosales-Pérez, Salvador García, Francisco Herrera
The resulting optimization problem is a bilevel problem, where the lower level determines the support vectors and the upper level the hyperparameters.
1 code implementation • 5 Mar 2020 • Sergio González, Salvador García, Sheng-Tun Li, Robert John, Francisco Herrera
This paper proposes a new model based on Fuzzy k-Nearest Neighbors for classification with monotonic constraints, Monotonic Fuzzy k-NN (MonFkNN).
no code implementations • 19 Feb 2020 • Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera
From our analysis, we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior.
no code implementations • 16 Jan 2020 • Diego García-Gil, Salvador García, Ning Xiong, Francisco Herrera
Ensembles have shown to be able to successfully address imbalanced data problems.
1 code implementation • 22 Oct 2019 • Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-López, Daniel Molina, Richard Benjamins, Raja Chatila, Francisco Herrera
In the last years, Artificial Intelligence (AI) has achieved a notable momentum that may deliver the best of expectations over many application sectors across the field.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +1
no code implementations • 14 Dec 2018 • Juan Luis Suárez-Díaz, Salvador García, Francisco Herrera
This tutorial provides a theoretical background and foundations on this topic and a comprehensive experimental analysis of the most-known algorithms.
no code implementations • 29 Nov 2018 • David Charte, Francisco Charte, Salvador García, Francisco Herrera
This field is subdivided into multiple areas, among which the best known are supervised learning (e. g. classification and regression) and unsupervised learning (e. g. clustering and association rules).
no code implementations • 17 Nov 2018 • José-Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michał Woźniak, Salvador García
Currently, knowledge discovery in databases is an essential step to identify valid, novel and useful patterns for decision making.
no code implementations • 23 Oct 2018 • M. Cristina Heredia-Gómez, Salvador García, Pedro Antonio Gutiérrez, Francisco Herrera
The classification and pre-processing of this type of data is attracting more and more interest in the area of machine learning, due to its presence in many common problems.
no code implementations • 21 Oct 2018 • José-Ramón Cano, Julián Luengo, Salvador García
Changing the class labels of the data set (relabelling) is useful for this.
1 code implementation • 14 Oct 2018 • Alejandro Alcalde-Barros, Diego García-Gil, Salvador García, Francisco Herrera
Data preprocessing techniques are devoted to correct or alleviate errors in data.
1 code implementation • 16 Apr 2018 • Sergio Ramírez-Gallego, Salvador García, Ning Xiong, Francisco Herrera
Empirical tests performed on our method show its estimation ability in manifold huge sets --both in number of features and instances--, as well as its simplified runtime cost (specially, at the redundancy detection step).
1 code implementation • 4 Jan 2018 • David Charte, Francisco Charte, Salvador García, María J. del Jesus, Francisco Herrera
Many of the existing machine learning algorithms, both supervised and unsupervised, depend on the quality of the input characteristics to generate a good model.
no code implementations • 6 Apr 2017 • Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera
In any knowledge discovery process the value of extracted knowledge is directly related to the quality of the data used.
no code implementations • 21 Mar 2017 • Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, Jose M. Benitez, Francisco Herrera
In our experiments, convolutional neural networks yielded better accuracy and penetration rate than state-of-the-art classifiers based on explicit feature extraction.