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IWANN
2005
Springer

Heuristic Search over a Ranking for Feature Selection

10 years 3 months ago
Heuristic Search over a Ranking for Feature Selection
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in high dimensional data sets. Our method is based on the relevance and redundancy idea, in the sense that a ranked-feature is chosen if additional information is gained by adding it. This heuristic leads to considerably better accuracy results, in comparison to the full set, and other representative feature selection algorithms in twelve well–known data sets, coupled with notable dimensionality reduction.
Roberto Ruiz, José Cristóbal Riquelm
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where IWANN
Authors Roberto Ruiz, José Cristóbal Riquelme Santos, Jesús S. Aguilar-Ruiz
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