Hierarchical determination of feature relevancy for mixed data types
US7298906B2 · kind B2 · utility
2Cited by
1References
13Claims
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Key dates
| Filing date | Feb 28, 2005 |
| Grant date | Nov 20, 2007 |
| Priority date | — |
| Expiry date | Feb 16, 2026 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/24323
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for feature selection based on hierarchical local-region analysis of feature characteristics in a data set of mixed data type is provided. A data space associated with a mixed-type data set is partitioned into a hierarchy of plural local regions. A relationship metric (for example, a similarity correlation metric) is used to evaluate for each local region a relationship measure between input features and a target. One or more relevant features is identified, by using the relationship measure for each local region.
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