A Tutorial on Multilabel Learning

被引：549

作者：

Gibaja, Eva ^{[1
]}

Ventura, Sebastian ^{[1
,2
]}

机构：

[1] Univ Cordoba, Dept Comp Sci & Numer Anal, E-14071 Cordoba, Spain

[2] King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Comp Sci, Jeddah 21413, Saudi Arabia

来源：

ACM COMPUTING SURVEYS | 2015年 / 47卷 / 03期

关键词：

Algorithms; Experimentation; Theory; Multilabel learning; ranking; classification; machine learning; data mining; LABEL CLASSIFICATION; DECISION TREES; OBJECT RECOGNITION; FEATURE-SELECTION; ALGORITHMS; FRAMEWORK; MACHINE; STRATEGIES; PREDICTION; RETRIEVAL;

D O I：

10.1145/2716262

中图分类号：

TP301 [理论、方法];

学科分类号：

080201 [机械制造及其自动化];

摘要：

Multilabel learning has become a relevant learning paradigm in the past years due to the increasing number of fields where it can be applied and also to the emerging number of techniques that are being developed. This article presents an up-to-date tutorial about multilabel learning that introduces the paradigm and describes the main contributions developed. Evaluation measures, fields of application, trending topics, and resources are also presented.

引用

页数：38

共 183 条

[1]

Pattern classification of dermoscopy images: A perceptually uniform model [J].

Abbas, Qaisar ;

Celebi, M. E. ;

Serrano, Carmen ;

Fondon Garcia, Irene ;

Ma, Guangzhi .

PATTERN RECOGNITION, 2013, 46 (01) :86-97

[2]

Aiolli Fabio, 2004, THESIS U STUDI PISA

[3]

Incorporating label dependency into the binary relevance framework for multi-label classification [J].

Alvares-Cherman, Everton ;

Metz, Jean ;

Monard, Maria Carolina .

EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (02) :1647-1655

[4]

[Anonymous], 2009, Advances in Neural Information Processing Systems (NIPS)

[5]

[Anonymous], CHEM BIO INF J

[6]

[Anonymous], 2007, Proceedings of the ACM international conference on Multimedia, DOI DOI 10.1145/1291233.1291245

[7]

[Anonymous], 2007, P 1 LINGUISTIC ANNOT

[8]

[Anonymous], 2006, Advances in Neural Information Processing Systems

[9]

[Anonymous], P 10 SIAM INT C DAT

[10]

[Anonymous], RES COMPUT SCI

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