Optimization approach for feature selection in multi-label classification-Reference-Cited by-同舟云学术

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Optimization approach for feature selection in multi-label classification

Published:2017-04 Issue: Volume:89 Page:25-30
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Lim Hyunki,Lee Jaesung,Kim Dae-Won

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference18 articles.

1. Document transformation for multi-label feature selection in text categorization;Chen,2007

2. Protein classification with multiple algorithms;Diplaris,2005

3. An interior-point method for large-scale-regularized least squares;Kim;IEEE J. Sel. Top. Signal Process.,2007

4. The Enron Corpus: a new dataset for email classification research;Klimt,2004

5. Multi-label relieff and f-statistic feature selections for image annotation;Kong,2012

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3. Fuzzy Neighborhood-Based Manifold Learning and Feature Weight Matrix for Multilabel Feature Selection;Knowledge-Based Systems;2024-09

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