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Ignacio Rojas
Researcher at University of Granada
Publications - 334
Citations - 6315
Ignacio Rojas is an academic researcher from University of Granada. The author has contributed to research in topics: Fuzzy logic & Fuzzy control system. The author has an hindex of 36, co-authored 321 publications receiving 5459 citations. Previous affiliations of Ignacio Rojas include ETH Zurich & Helsinki University of Technology.
Papers
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Journal ArticleDOI
Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification
Jose Urquiza,Ignacio Rojas,Héctor Pomares,J. Herrera,Javier Florido,Olga Valenzuela,Maria del Mar Cepero +6 more
TL;DR: A new approach is proposed to PPI data classification based on the extraction of genomic and proteomic information from well-known databases and the incorporation of semantic measures, which provides very accurate models with high levels of sensitivity and specificity in the classification of PPIs.
Journal Article
SSA, SVD, QR-cp, and RBF model reduction
TL;DR: In this paper, the authors proposed an application of SVD model reduction to the class of RBF neural models for improving performance in contexts such as on-line prediction of time series.
Book ChapterDOI
High-Level Context Inference for Human Behavior Identification
Claudia Villalonga,Oresti Banos,Wajahat Ali Khan,Taqdir Ali,Muhammad Asif Razzaq,Sungyoung Lee,Héctor Pomares,Ignacio Rojas +7 more
TL;DR: The Mining Minds Context Ontology is shown to be flexible enough to operate in real life scenarios in which emotion recognition systems may not always be available, and to demonstrate that the activity and the location might not be enough to detect some of the high-level contexts.
Journal ArticleDOI
Decision Support System to Determine Intention to Use Mobile Payment Systems on Social Networks: A Methodological Analysis
Alberto Guillén,Luis Javier Herrera,Héctor Pomares,Ignacio Rojas,Francisco Liébana-Cabanillas +4 more
TL;DR: The paper includes a comparative analysis of several machine learning methods applied to the variable selection problem considering strategic, sociodemographic, and behavioral variables and proposes a novel approach using multiobjective optimization criteria.
Proceedings Article
Applying Mutual Information for Prototype or Instance Selection in Regression Problems
Alberto Guillén,Luis Javier Herrera,Ginés Rubio,Héctor Pomares,Amaury Lendasse,Ignacio Rojas +5 more
TL;DR: A new application of the concept of mutual information not to select thevariables but to decide which prototypes should belong to the training dataset in regression problems, which is able to identify a high percentage of the real data set when it is applied to a highly distorted data sets.