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Appavu alias Balamurugan et al., 2018 - Google Patents

An efficient feature selection and classification using optimal radial basis function neural network

Appavu alias Balamurugan et al., 2018

Document ID
11639113001347477733
Author
Appavu alias Balamurugan S
Nancy S
Publication year
Publication venue
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

External Links

Snippet

Feature selection is the process of identifying and removing many irrelevant and redundant features. Irrelevant features, along with redundant features, severely affect the accuracy of the learning machines. In high dimensional space finding clusters of data objects is …
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Classifications

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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
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    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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    • G06K9/6228Selecting the most significant subset of features
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    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
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