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Conference Papers Year : 2019

A Feature Selection Method based on Tree Decomposition of Correlation Graph

Abdelkader Ouali
Nyoman Juniarta
Bernard Maigret
  • Function : Author
  • PersonId : 885247
Amedeo Napoli

Abstract

This paper presents a new method for feature selection where only relevant features are kept in the dataset and all other features are discarded. The proposed method uses tree decomposition heuristics to reveal subsets of highly connected features. These subsets are replaced by selecting representatives to reduce feature redundancy. Experiments performed on various datasets show promising results for our proposals.
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Dates and versions

hal-02194229 , version 1 (25-07-2019)

Identifiers

  • HAL Id : hal-02194229 , version 1

Cite

Abdelkader Ouali, Nyoman Juniarta, Bernard Maigret, Amedeo Napoli. A Feature Selection Method based on Tree Decomposition of Correlation Graph. LEG@ECML-PKDD 2019 - The third International Workshop on Advances in Managing and Mining Large Evolving Graphs, Sep 2019, Würzburg, Germany. ⟨hal-02194229⟩
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