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Semi-supervised Learning for Ordinal Kernel Discriminant Analysis
- Source :
- Brújula, Universidad Loyola Andalucía, Neural Networks 84, 57-66 (2016), Helvia. Repositorio Institucional de la Universidad de Córdoba, instname
- Publication Year :
- 2016
-
Abstract
- Ordinal classication considers those classication problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or di_cult to obtain in this type of problems because, in many cases, ordinal labels are given by an user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classi_cation where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classi_cation, which is combined with our developed classi_cation strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classication in a battery of 30 datasets, showing 1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and 2) the advantage of computing distances in the feature space induced by the kernel function.
- Subjects :
- Ordinal data
Computer Science::Machine Learning
Cognitive Neuroscience
Classi cation
02 engineering and technology
Semi-supervised learning
Machine learning
computer.software_genre
Ordinal regression
Artificial Intelligence
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Mathematics
Spatial Analysis
business.industry
Kernel learning
Discriminant Analysis
Pattern recognition
Classification
Discriminant analysis
Statistical classification
ComputingMethodologies_PATTERNRECOGNITION
Kernel embedding of distributions
Kernel (statistics)
Radial basis function kernel
020201 artificial intelligence & image processing
Artificial intelligence
Supervised Machine Learning
Kernel Fisher discriminant analysis
business
Classication
computer
Algorithms
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Brújula, Universidad Loyola Andalucía, Neural Networks 84, 57-66 (2016), Helvia. Repositorio Institucional de la Universidad de Córdoba, instname
- Accession number :
- edsair.doi.dedup.....d6bc08505839a643c71a812ba548e0d9