Classifier chains for multi-label classification

Author： Read Jesse Pfahringer Bernhard Holmes Geoff Frank Eibe

ISSN： 0885-6125

Source： Machine Learning, Vol.85, Iss.3, 2011-12, pp. : 333-359

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

On label dependence and loss minimization in multi-label classification

By Dembczyński Krzysztof Waegeman Willem Cheng Weiwei Hüllermeier Eyke

Machine Learning, Vol. 88, Iss. 1-2, 2012-07 ,pp. : 5-45

Springer Publishing Company

Access to resources Recommend Favorite

Statistical topic models for multi-label document classification

By Rubin Timothy Chambers America Smyth Padhraic Steyvers Mark

Machine Learning, Vol. 88, Iss. 1-2, 2012-07 ,pp. : 157-208

Springer Publishing Company

Access to resources Recommend Favorite

Efficient max-margin multi-label classification with applications to zero-shot learning

By Hariharan Bharath Vishwanathan S. Varma Manik

Machine Learning, Vol. 88, Iss. 1-2, 2012-07 ,pp. : 127-155

Springer Publishing Company

Access to resources Recommend Favorite

Scalable and efficient multi-label classification for evolving data streams

By Read Jesse Bifet Albert Holmes Geoff Pfahringer Bernhard

Machine Learning, Vol. 88, Iss. 1-2, 2012-07 ,pp. : 243-272

Springer Publishing Company

Access to resources Recommend Favorite

Multi-Label Naïve Bayes Classifier for Identification of Top Destination and Issues to Accost by Tourism Sector

Journal of Global Information Management (JGIM), Vol. 26, Iss. 3, 2018-07 ,pp. : 37-53

IGI Global_journal

Access to resources Recommend Favorite