Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Multi-Label Classification using MUENL Approach


Affiliations
1 Department of Computer Science, GATE College, Tirupati, Andhra Pradesh, India
     

   Subscribe/Renew Journal


In a multi-mark acing challenge, a lump of creating has varying mind the see each concept is tended to with the guide of approach for a category seize. Earlier appraisals on multi-understand gaining knowledge of have fixated on a fi xed set of improvement marks, i.e., the type perceive set of looks at realities seems like that in the reputation set. In endless bundles, be that as its miles preserving a key accurate approach from to, the earth is dynamic and new suggestions can also upgrade in a getting manner. As a way to deal with display up a good savvy comply with up proper now, multi-mark considering method needs to be in a circumstance to famed and layout styles with growing new names. To this stop, we advise an in addition approach alluded to as Multi-mark getting realities on with rising New Labels (MUENL) [1, 2, 3].

Keywords

Developing New Names, Examine Product, Getting the Preserve of, Multi-Mark Locating an Awesome Tempo.
Subscription Login to verify subscription
User
Notifications
Font Size


  • W. Bi, and J. T. Kwok, “Multilabel classification with label correlations and missing labels,” In Proc. 28th AAAI Conf. Artif. Intell., 2014, pp. 1680-1686.
  • N. Boumal, B. Mishra, P.-A. Absil, and R. Sepulchre, “Manopt, a Matlab toolbox for optimization on manifolds,” Journal of Machine Learning Research, vol. 15, pp. 1455-1459, 2014.
  • M. R. Boutell, J. Luo, X. Shen, and C. M. Brown, “Learning multilabel scene classification,” Pattern Recognition, vol. 37, no. 9, pp. 1757-1771, 2004.
  • Q. Da, Y. Yu, and Z.-H. Zhou, “Learning with augmented class by exploiting unlabeled data,” In Proc. of 28th AAAI Conf. Artif. Intell., 2014, pp. 1760-1766.
  • R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin, “LIBLINEAR: A library for large linear classification,” Journal of Machine Learning Research, vol. 9, pp. 1871-1874, 2008.
  • Y. Fu, Y. Yang, T. Hospedales, T. Xiang, and S. Gong, “Transductive multi-label zero-shot learning,” 2015. arXiv preprint arXiv:1503.07790.
  • J. Fürnkranz, E. Hüllermeier, E. L. Mencía, and K. Brinker, “Multilabel classification via calibrated label ranking,” Machine Learning, vol. 73, no. 2, pp. 133-153, 2008.
  • M. Ghashami, D. J. Perry, and J. Phillips, “Streaming kernel principal component analysis,” In Proc. 19th Int. Conf. Artif. Intell. and Statist, 2016, pp. 1365-1374.
  • Y. Gong, Q. Zhang, X. Han, and X. Huang, “Phrase-based hashtag recommendation for microblog posts,” SCIENCE CHINA Information Sciences, vol. 60, no. 1, pp. 12109:1-12109:13, 2017.
  • M. Hollander, D. A. Wolfe, and E. Chicken, Nonparametric Statistical Methods, John Wiley & Sons, 2013.
  • S.-J. Huang, and Z.-H. Zhou, “Multi-label learning by exploiting label correlations locally,” In Proc. 26th AAAI Conf. Artif. Intell., 2012, pp. 949-955.
  • V. Jain, N. Modhe, and P. Rai, “Scalable generative models for multi-label learning with missing labels,” In Proc. 34th Int. Conf. Mach. Learn., 2017, pp. 1636-1644.

Abstract Views: 8

PDF Views: 0




  • Multi-Label Classification using MUENL Approach

Abstract Views: 8  |  PDF Views: 0

Authors

Jyothi Darapuneni
Department of Computer Science, GATE College, Tirupati, Andhra Pradesh, India

Abstract


In a multi-mark acing challenge, a lump of creating has varying mind the see each concept is tended to with the guide of approach for a category seize. Earlier appraisals on multi-understand gaining knowledge of have fixated on a fi xed set of improvement marks, i.e., the type perceive set of looks at realities seems like that in the reputation set. In endless bundles, be that as its miles preserving a key accurate approach from to, the earth is dynamic and new suggestions can also upgrade in a getting manner. As a way to deal with display up a good savvy comply with up proper now, multi-mark considering method needs to be in a circumstance to famed and layout styles with growing new names. To this stop, we advise an in addition approach alluded to as Multi-mark getting realities on with rising New Labels (MUENL) [1, 2, 3].

Keywords


Developing New Names, Examine Product, Getting the Preserve of, Multi-Mark Locating an Awesome Tempo.

References