Heat Map Based Feature Ranker: In depth comparison with popular methods-Reference-Cited by-同舟云学术

Heat Map Based Feature Ranker: In depth comparison with popular methods

Published:2018-09-26 Issue:5 Volume:22 Page:1009-1037
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Huertas Carlos¹,Juarez-Ramirez Reyes¹,Raymond Christian²

Affiliation:

1. Universidad Autonoma de Baja California, Tijuana, Mexico

2. Institut de Recherche en Informatique et Systemes Aleatoires, Rennes Cedex, France

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference31 articles.

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4. Conditional likelihood maximisation: A unifying framework for information theoretic feature selection;Brown;J. Mach. Learn. Res.,2012

5. S. Das, Filters, wrappers and a boosting-based hybrid for feature selection, in: Proceedings of the Eighteenth International Conference on Machine Learning, San Francisco, CA, USA, 2001, ICML ’01, Morgan Kaufmann Publishers Inc., pp. 74–81.

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