Empowering difficult classes with a similarity-based aggregation in multi-class classification problems

DOI10.1016/j.ins.2013.12.053zbMath1335.68201OpenAlexW2150932143MaRDI QIDQ278697

Mikel Galar, Alberto Fernández, Edurne Barrenechea, Francisco Herrera

Publication date: 2 May 2016

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2013.12.053

zbMATH Keywords

tuningmulti-class classificationone-vs-onepairwise learningdecomposition strategiesdifficult classes

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

Enhancing evolutionary fuzzy systems for multi-class problems: distance-based relative competence weighting with truncated confidences (DRCW-TC) ⋮ Managing incomplete preference relations in decision making: a review and future trends ⋮ Capacities and overlap indexes with an application in fuzzy rule-based classification systems ⋮ Basic co-occurrence latent semantic vector space model

Uses Software

• UCI-ml
• JStatCom
• KEEL
• C4.5

Cites Work

• Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations
• Naive Bayesian classification of structured data
• Combining predictions in pairwise classification: an optimal adaptive voting strategy and its relation to weighted voting
• Data complexity in pattern recognition.
• Restricted equivalence functions
• Image thresholding using restricted equivalence functions and maximizing the measures of similarity
• Tree induction for probability-based ranking
• 10.1162/15324430152733133
• 10.1162/153244302320884605
• Interval-Valued Fuzzy Sets Applied to Stereo Matching of Color Images
• Evaluating Learning Algorithms
• Robust classification for imprecise environments
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