Improved support vector machine algorithm for heterogeneous data

DOI10.1016/j.patcog.2014.12.015zbMath1374.68415OpenAlexW2079110736MaRDI QIDQ1678705

Shili Peng, Yinli Chen, Qinghua Hu, Jianwu Dang

Publication date: 20 November 2017

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2014.12.015

zbMATH Keywords

support vector machineheterogeneous dataclassification learningnominal attributenumerical attribute

Mathematics Subject Classification ID

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

Related Items

The Choquet kernel on the use of regression problem, A neighborhood rough set model with nominal metric embedding, Support vector machine with Dirichlet feature mapping, Multi-class support vector machine classifiers using intrinsic and penalty graphs, Model-aware categorical data embedding: a data-driven approach, Research on the matching algorithm for heterologous image after deformation in the same scene

Uses Software

• UCI-ml
• LIBSVM
• Maude
• WEKA

Cites Work

• Multi-model classification method in heterogeneous image databases
• SpectralCAT: categorical spectral clustering of numerical and nominal data
• A survey of content-based image retrieval with high-level semantics
• Active learning for image retrieval with Co-SVM
• Handwritten digit recognition: Benchmarking of state-of-the-art techniques.
• Cascade generalization
• Clustering of time series data -- a survey
• Discriminatory Analysis. Nonparametric Discrimination: Consistency Properties
• Choosing multiple parameters for support vector machines
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