Multi-label Learning Linearity in Ensemble of Pruned Set
Author:
Affiliation:
1. Technological Institute of the Philippines, Quezon City, Philippines
2. Manuel L. Quezon University, Quezon City, Philippines
Publisher
ACM
Reference52 articles.
1. A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine
2. Xu D. Shi Y. Tsang I. Ong Y. Gong C. and Shen X. 2019. A Survey on Multi-output Learning. Web published in Cornel University. Xu D. Shi Y. Tsang I. Ong Y. Gong C. and Shen X. 2019. A Survey on Multi-output Learning. Web published in Cornel University.
3. Moyano J. Gibaja E. Cios K. and Ventura S. 2018. Review of ensembles of multi-label classifiers: Models experimental study and prospects. An international journal in Information Fusion Science Direct. Moyano J. Gibaja E. Cios K. and Ventura S. 2018. Review of ensembles of multi-label classifiers: Models experimental study and prospects. An international journal in Information Fusion Science Direct.
4. Benrekia N. Kuntz P. and Meyer F. 2015. Learning from multi-label data with interactivity constraints: An extensive experimental study. Expert Systems with Applications. Benrekia N. Kuntz P. and Meyer F. 2015. Learning from multi-label data with interactivity constraints: An extensive experimental study. Expert Systems with Applications.
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