Feature Selection and Multiple Model Approach in Discriminant Analysis

• Authors: Gatnar, Eugeniusz

Title variants

EN

Dobór zmiennych a podejście wielomodelowe w analizie dyskryminacyjnej

Abstracts

EN

Significant improvement of model stability and prediction accuracy in classification and regression can be obtained by using the multiple model approach. In classification multiple models are built on the basis of training subsets (selected from the training set) and combined into an ensemble or a committee. Then the component models (classification trees) determine the predicted class by voting. In this paper some problems of feature selection for ensembles will be discussed. We propose a new correlation-based feature selection method combined with the wrapper approach.

Keywords

EN

tree-based models; aggregation; feature selection; random subspaces

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2007
• Volume: 206

Dates

published

2007

Contributors

author

Gatnar, Eugeniusz

other

Katowice University of Economics, Institute of Statistics

Identifiers

URI

http://hdl.handle.net/11089/16836