A simple and effective scheme for data pre-processing in extreme classification

Sujay Khandagale; Rohit Babbar

A simple and effective scheme for data pre-processing in extreme classification

Sujay Khandagale, Rohit Babbar

Department of Computer Science

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

1 Citation (SciVal)

Abstract

Extreme multi-label classification (XMC) refers to supervised multi-label learning involving hundreds of thousand or even millions of labels. It has been shown to be an effective framework for addressing crucial tasks such as recommendation, ranking and web-advertising. In this paper, we propose a method for effective and well-motivated data pre-processing scheme in XMC. We show that our proposed algorithm, PrunEX, can remove upto 90% data in the input which is redundant from a classification view-point. Our scheme is universal in the sense it is applicable to all known public datasets in the domain of XMC.

Original language	English
Title of host publication	ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Publisher	ESANN (i6doc.com)
Pages	67-72
Number of pages	6
ISBN (Electronic)	9782875870650
Publication status	Published - 26 Apr 2019
Event	27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019 - Bruges, Belgium Duration: 24 Apr 2019 → 26 Apr 2019

Publication series

Name	ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Conference

Conference	27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019
Country/Territory	Belgium
City	Bruges
Period	24/04/19 → 26/04/19

Bibliographical note

Funding Information:
This work was done when Sujay was a student at Aalto University, Finland We appreciate the computing resources provided by the Aalto Science-IT project.

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

Cite this

Khandagale, S., & Babbar, R. (2019). A simple and effective scheme for data pre-processing in extreme classification. In ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 67-72). (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning). ESANN (i6doc.com).

A simple and effective scheme for data pre-processing in extreme classification. / Khandagale, Sujay; Babbar, Rohit.
ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com), 2019. p. 67-72 (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Khandagale, S & Babbar, R 2019, A simple and effective scheme for data pre-processing in extreme classification. in ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN (i6doc.com), pp. 67-72, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019, Bruges, Belgium, 24/04/19.

Khandagale S, Babbar R. A simple and effective scheme for data pre-processing in extreme classification. In ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com). 2019. p. 67-72. (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Khandagale, Sujay ; Babbar, Rohit. / A simple and effective scheme for data pre-processing in extreme classification. ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN (i6doc.com), 2019. pp. 67-72 (ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

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A simple and effective scheme for data pre-processing in extreme classification

Abstract

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Bibliographical note

ASJC Scopus subject areas

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