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Firpi et al., 2004 - Google Patents

Swarmed feature selection

Firpi et al., 2004

Document ID
6806318364318428701
Author
Firpi H
Goodman E
Publication year
Publication venue
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)

External Links

Snippet

Feature selection is an important part of pattern recognition, helping to overcome the curse of dimensionality problem with classifiers, among other systems. In this work, we introduce a feature selection method using particle swarm optimization. Experiments using data of …
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Classifications

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    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627—Classification 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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    • G06K9/6228—Selecting the most significant subset of features
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