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Guo, 2009 - Google Patents

An integrated PSO for parameter determination and feature selection of SVR and its application in STLF

Guo, 2009

Document ID
3827447190667991713
Author
Guo Y
Publication year
Publication venue
2009 International Conference on Machine Learning and Cybernetics

External Links

Snippet

A novel support vector regression (SVR) optimized by an integrated particle swarm optimization (PSO) was proposed. The optimization mechanism combined the discrete- valued PSO with the continuous-valued PSO to optimize the input feature subset selection …
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Classifications

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    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
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    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/6269—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on the distance between the decision surface and training patterns lying on the boundary of the class cluster, e.g. support vector machines
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    • G—PHYSICS
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    • G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
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