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ICML
2001
IEEE

Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection

10 years 4 months ago
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection
In this paper, we examine the advantages and disadvantages of filter and wrapper methods for feature selection and propose a new hybrid algorithm that uses boosting and incorporates some of the features of wrapper methods into a fast filter method for feature selection. Empirical results are reported on six real-world datasets from the UCI repository, showing that our hybrid algorithm is competitive with wrapper methods while being much faster, and scales well to datasets with thousands of features.
Sanmay Das
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2001
Where ICML
Authors Sanmay Das
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