Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality

Roffo, G. and Melzi, S. (2017) Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality. In: Appice, A., Ceci, M., Loglisci, C., Masciari, E. and Ras, Z. (eds.) New Frontiers in Mining Complex Patterns: 5th International Workshop, NFMCP 2016, held in Conjunction with ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016, Revised Selected Papers. Series: Lecture Notes in Artificial Intelligence (10312). Springer, pp. 19-35. ISBN 9783319614618

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Publisher's URL: http://www.springer.com/gb/book/9783319614601

Abstract

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Item Type:Book Sections
Status:Published
Glasgow Author(s) Enlighten ID:Roffo, Dr Giorgio
Authors: Roffo, G., and Melzi, S.
College/School:College of Science and Engineering > School of Computing Science
Publisher:Springer
ISBN:9783319614618

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