Hierarchical determination of feature relevancy
First Claim
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1. A method for feature selection based on hierarchical local-region analysis of feature characteristics in a data set, comprising:
- partitioning a data space associated with a data set into a hierarchy of pluralities of local regions;
using a similarity metric to evaluate for each local region a relationship measure between input features and a selected output feature; and
identifying one or more relevant features, by using the relationship measure for each local region.
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Abstract
Methods for feature selection based on hierarchical local-region analysis of feature relationships in a data set are provided.
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Citations
28 Claims
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1. A method for feature selection based on hierarchical local-region analysis of feature characteristics in a data set, comprising:
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partitioning a data space associated with a data set into a hierarchy of pluralities of local regions;
using a similarity metric to evaluate for each local region a relationship measure between input features and a selected output feature; and
identifying one or more relevant features, by using the relationship measure for each local region. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A method for feature selection based on hierarchical local-region analysis of feature characteristics in a data set, comprising:
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partitioning a data space corresponding to a data set into a hierarchy of pluralities of local regions;
on each level of the hierarchy, using a similarity metric to evaluate for each local region in the level a relationship measure between input feature values on the one hand and a selected output on the other hand; and
determining a relevancy of a selected feature by performing a weighted sum of the relationship measures for the feature over the plurality of local regions at appropriate levels. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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Specification