Show simple item record

dc.contributor.authorGonzález, Manuel
dc.contributor.authorGarcía, Salvador
dc.identifier.citationGonzález, M., Cano, J. R., & García, S. (2020). ProLSFEO-LDL: Prototype Selection and Label-Specific Feature Evolutionary Optimization for Label Distribution Learning. Applied Sciences, 10(9), 3089. [doi:10.3390/app10093089]es_ES
dc.description.abstractLabel Distribution Learning (LDL) is a general learning framework that assigns an instance to a distribution over a set of labels rather than to a single label or multiple labels. Current LDL methods have proven their effectiveness in many real-life machine learning applications. In LDL problems, instance-based algorithms and particularly the adapted version of the k-nearest neighbors method for LDL (AA-kNN) has proven to be very competitive, achieving acceptable results and allowing an explainable model. However, it suffers from several handicaps: it needs large storage requirements, it is not efficient predicting and presents a low tolerance to noise. The purpose of this paper is to mitigate these effects by adding a data reduction stage. The technique devised, called Prototype selection and Label-Specific Feature Evolutionary Optimization for LDL (ProLSFEO-LDL), is a novel method to simultaneously address the prototype selection and the label-specific feature selection pre-processing techniques. Both techniques pose a complex optimization problem with a huge search space. Therefore, we have proposed a search method based on evolutionary algorithms that allows us to obtain a solution to both problems in a reasonable time. The effectiveness of the proposed ProLSFEO-LDL method is verified on several real-world LDL datasets, showing significant improvements in comparison with using raw datasets.es_ES
dc.description.sponsorshipThis work is supported by the Spanish National Research Project TIN2017-89517-P.es_ES
dc.rightsAtribución 3.0 España*
dc.subjectLabel distribution learninges_ES
dc.subjectEvolutionary optimizationes_ES
dc.subjectProtoype selectiones_ES
dc.subjectLabel-specific featurees_ES
dc.subjectMachine learninges_ES
dc.titleProLSFEO-LDL: Prototype Selection and LabelSpecific Feature Evolutionary Optimization for Label Distribution Learninges_ES

Files in this item


This item appears in the following Collection(s)

Show simple item record

Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España