LPIS Home Page
Google Search

Title: Mining Multi-label Data
Author(s): G. Tsoumakas, I. Katakis, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (19 pages).
Keywords:
Appeared in: Data Mining and Knowledge Discovery Handbook, Part 6, O. Maimon, L. Rokach (Ed.), Springer, 2nd edition, pp. 667-685, 2010.
Abstract:
See also : Mining from multi-label data web page @ MLKD


        This paper has been cited by the following:

1 Villalba, S.D., Cunningham, P. (2009) Using Unsupervised Classifiers for Multilabel Classification in Open-Class-Set Scenarios, Proceedings of the ECML/PKDD 2009 Workshop on Learning from Multi-Label Data (MLD09), pp. 146-160, Bled, Slovenia, September 2009.
2 Qu, W., Zhang, Y., Zhu, J., Qiu, Q. (2009) Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble, 1st Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009, pp. 308-321.
3 Tsai, S.-C., Jiang, J.-Y., Wu, C., Lee, S.-J. (2009) A Fuzzy Similarity-Based Approach for Multi-label Document Classification, Proc. 2nd International Workshop on Computer Science and Engineering, pp. 59-63
4 Gantner, Z, Thieme, L.-S., (2009) Automatic Content-based Categorization of Wikipedia Articles, Proceedings of the 2009 Workshop on the Peoples Web Meets NLP, ACL-IJCNLP 2009, pages 3237, Suntec, Singapore, 7 August 2009
5 Gibaja, E., Victoriano, M., vila-Jimnez, J.L., Ventura, S. (2010) A TDIDT technique for multi-label classification, Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10, art. no. 5687213, pp. 519-524.
6 Ahsan, S. N. and Wotawa, F. (2010). Impact analysis of SCRs using single and multi-label machine learning classification. In Proceedings of the 2010 ACM-IEEE international Symposium on Empirical Software Engineering and Measurement (Bolzano-Bozen, Italy, September 16 - 17, 2010). ESEM '10. ACM, New York, NY, 1-4.
7 Santos, A.M., Santana, L.E.A., Canuto, A.M. (2010) Analyzing Classification Methods in Multi-label Tasks, Proc. ICANN 2010, Lecture Notes in Computer Science, 2010, Volume 6354/2010, 137-142
8 Kouzani, A. (2010) Multilabel Classification Using Error Correction Codes, Proc. 5th International Symposium, ISICA 2010, Wuhan, China, October 22-24, 2010, pp. 444-454.
9 Read, J. (2010) Scalable Multi-Label Classification, PhD Thesis, University of Waikato.
10 Li, G.-Z., You, M., Ge, L., Yang, J.Y., Yang, M.Q. (2010) Feature selection for semi-supervised multi-label learning with application to gene function analysis, 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010, pp. 354-357.
11 Cherman, E.A., Metz, J., Monard, M.C. (2010) A Simple Approach to Incorporate Label Dependency in Multi-label Classification, Proc. 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Pachuca, Mexico, November 8-13, 2010, pp. 33-43.
12 Guo-Ping Liu, Guo-Zheng Li, Ya-Lei Wang, Yi-Qin Wang (2010) Modelling of inquiry diagnosis for coronary, heart disease in traditional Chinese medicine by using multi-label learning. BMC Complementary and Alternative Medicine 2010 10:37.
13 Luna De Ferrari, Stuart Aitken, Jano van Hemert and Igor Goryanin (2010) Multi-label prediction of enzyme classes using InterPro signatures, Proc. Fourth International Workshop on Machine Learning in Systems Biology, pp. 123-127,
14 Nasierding, G., Kouzani, A.Z. (2010) "Empirical Study of Multi-label Classification Methods for Image Annotation and Retrieval," dicta, pp.617-622, 2010 International Conference on Digital Image Computing: Techniques and Applications.
15 Petterson, J., Caetano, T. (2010) Reverse Multi-Label Learning, Advances in Neural Information Processing Systems 23 (NIPS 2010), pp 1912-1920.
16 Menca, E.L (2010) An Evaluation of Multilabel Classification for the Automatic Annotation of Texts, Proceedings of the LWA 2010: Lernen, Wissen and Adaptivitt, Workshop on Knowledge Discovery and Machine Learning (KDML 2010), pp. 121-123
17 Santos, A.M., Canuto, A.M.P., Neto, A.F. (2010) Evaluating classification methods applied to multi-label tasks in different domains, 10th International Conference on Hybrid Intelligent Systems, HIS 2010, art. no. 5600014, pp. 61-66.
18 Lin, X., Chen, X.-W. (2010) Mr.KNN: soft relevance for multi-label classification. In Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10). ACM, New York, NY, USA, 349-358.
19 Rokach, L, Itachm E. (2010) An Ensemble Method for Multi-label Classification using an Approximation Algorithm for the Set Covering Problem, Proc. 2nd International Workshop on Multi-Label Learning.
20 Zhang, X., Yuan, Q., Zhao, S., Fan, W. Zheng, W., Wang, Z. (2010) Multi-Label Classification Without Multi-Label Cost, Proc. 2010 SIAM International Conference on Data Mining (SDM 2010), pp. 778-789.
21 Sanden,C. (2010) An Empirical Evaluation of Computational and Perceptual Multi-Label Genre Classification on Music, Master Thesis, Department of Mathematics and Computer Science, University of Lethbridge, Canada.
22 Wicker, J., Fenner, K., Ellis, L., Wackett, L., Kramer, S. (2010) Predicting biodegradation products and pathways: A hybrid knowledge- and machine learning-based approach, Bioinformatics, 26 (6), art. no. btq024, pp. 814-821.
23 Dembczynski, K., Waegeman, W., Cheng W., Hllermeier, E. (2010) Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss, Proc. European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, pp. 280-295
24 Lin, Y.-X., Chien, B.-C. (2010) A discriminant based document analysis for text classification, ICS 2010 - International Computer Symposium, art. no. 5685442, pp. 594-599.
25 Loza Mencia, E. (2010), Multilabel Classification in Parallel Tasks, Proc. 2nd International Workshop on Multi-Label Learning.
26 Heath, D., Zitzelberger, A., Giraud-Carrier, C.G. (2010) A Multiple Domain Comparison of Multi-label Classification Methods, Proc 2nd International Workshop on Learning from Multi-Label Data.
27 Tai, F, Lin H.-T. (2010) Multi-Label Classification with Principle Label Space Transformation, Proc. 2nd International Workshop on Multi-Label Learning.
28 Tenenboim-Chekina, L., Rokach, L., Shapira, B. (2010) Identification of Label Dependencies for Multi-label Classification, Proc. 2nd International Workshop on Multi-Label Learning.
29 Ahsan, S.N., Ferzund, J., Wotawa, F. (2010) Automatic classification of software change request using multi-label machine learning methods, Proceedings - 33rd Annual IEEE Software Engineering Workshop, SEW-33 2009, art. no. 5621702, pp. 79-86.
30 Vogrincic, S., Bosnic, Z. (2010) Multi-label Document Classification Based on the Economic Ontology, Proc. 2nd International Workshop on Multi-Label Learning.
31 Zhang, M. and Zhang, K. 2010. Multi-label learning by exploiting label dependency. In Proceedings of the 16th ACM SIGKDD international Conference on Knowledge Discovery and Data Mining (Washington, DC, USA, July 25 - 28, 2010). KDD '10. ACM, New York, NY, 999-1008.
32 Nasierding, G, Kouzani, A. (2010) Image to Text Translation by Multi-Label Classification, Proc. 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, August 18-21, 2010, pp. 247-254.
33 Tahir, M.A., Kittler, J., Mikolajczyk, K., Yan, F.(2010) Improving multilabel classification performance by using ensemble of multi-label classifiers, Proc. 9th International Workshop on Multiple Classifier Systems, MCS 2010, Cairo, Egypt, April 7-9, 2010, pp. 11-21.
34 Chin, S.-C., Street, W. N. (2011) Enriching Wikipedia vandalism taxonomy via subclass discovery, Proc. International Joint Conference on Artificial Intelligences (IJCAI) Workshop on Discovering Meaning on the Go in Large and Heterogeneous Data (LHD-11)
35 Guo, Y., Schuurmans, D. (2011) Adaptive large margin training for multilabel classification, Proceedings of the National Conference on Artificial Intelligence, 1, pp. 374-379.
36 Pillai, I., Fumera, G., Roli, F. (2011) Classifier Selection Approaches for Multi-label Problems, Proc. 10th International Workshop on Multiple Classifier Systems, MCS 2011.
37 G.-Z. Li. Chapter 9, Machine Learning for Clinical Data Processing, In: Andriani Daskalaki (Editor), Digital Forensics for the Health Sciences: Applications in Practice, IGI-global: Medical Info Science Reference, 2011, 193-215. ISBN13: (978-1-60960-483-7)
38 Choi, H., Zhu, B.B., Lee, H. (2011) Detecting Malicious Web Links and Identifying Their Attack Types, Proc. WebApps '11: 2nd USENIX Conference on Web Application Development.
39 Cherman, E.A., Metz, J., Monard, M.C. (2011) Multi-label Problem Transformation Methods: a Case Study, CLEI Electronic Journal, 14(1), paper 4.
40 Hindle, A., Ernst, N.A., Godfrey, M.W., Mylopoulos, J. (2011) Automated topic naming to support cross-project analysis of software maintenance activities, Proceedings - International Conference on Software Engineering, pp. 163-172.
41 Xiao-lin Wang, Hai Zhao, Bao-liang Lu (2011) Enhanced K-Nearest Neighbour Algorithm for Large-scale Hierarchical Multi-label Classification, Proc. Joint ECML/PKDD PASCAL Workshop on Large-Scale Hierarchical Classification, pp. 58-67.
42 Cour, T., Sapp, B., Taskar, B. (2011) Learning from Partial Labels, Journal of Machine Learning Research 12 (2011) 1501-1536
43 Hsu, M.-H., Chen, H.-H. (2011) Efficient and effective prediction of social tags to enhance web search, Journal of the American Society for Information Science and Technology, 62 (8), pp. 1473-1487.
44 Carmona-Cejudo, J.M., Baena-Garca, M., Campo-Avila, J.D., Morales-Bueno, R. (2011) Feature extraction for multi-label learning in the domain of email classification, IEEE SSCI 2011: Symposium Series on Computational Intelligence - CIDM 2011: 2011 IEEE Symposium on Computational Intelligence and Data Mining, art. no. 5949301, pp. 30-36.
45 Montas, E., Quevedo, J.R., del Coz, J.J. (2011) Aggregating Independent and Dependent Models to Learn Multi-label Classifiers, Proc. ECML PKDD 2011, part II, pp. 484-500.
46 Xu, J. (2011) An extended one-versus-rest support vector machine for multi-label classification, Neurocomputing, 74 (17), pp. 3114-3124.
47 Lo, H.-Y., Wang, J.-C., Wang, H.-M., Lin, S.-D. (2011), Cost-Sensitive Multi-Label Learning for Audio Tag Annotation and Retrieval, IEEE Transactions on Multimedia, vol.13, no.3, pp.518-529, June 2011
48 Naula, P., Pahikkala, T., Airola, A., Salakoski, T. (2011) Learning multi-label predictors under sparsity budget, Frontiers in Artificial Intelligence and Applications, 227, pp. 30-39.
49 Pillai, I., Fumera, G., Roli, F. (2011) A Classification Approach with a Reject Option for Multi-label Problems, 16th Int. Conf. on Image Analysis and Processing (ICIAP 2011), Ravenna, Italy.
50 Virtanen, S., Klami, A., Kaski, S. (2011) Bayesian CCA via group sparsity, Proceedings of the 28th International Conference on Machine Learning, ICML 2011, pp. 457-464.
51 Vivian F. Lpez Batista, Fernando Prieta Pintado, Ana Beln Gil, Sara Rodrguez and Mara N. Moreno (2011) A System for Multi-label Classification of Learning Objects, Proc. 6th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2011, pp. 523-531.
52 Bielza, C., Li, G., Larraaga, P. Multi-dimensional classification with Bayesian networks (2011) International Journal of Approximate Reasoning, 52 (6), pp. 705-727.
53 Zhang, Y., Schneider, J. (2011) Multi-label Output Codes using Canonical Correlation Analysis, AISTATS 2011
54 A.J. Rivera, F. Charte, M.D. Prez-Godoy, M.J. del Jesus. (2011) Multi-label testing for CO2RBFN. A first approach to the problem transformation methodology for multi-label classification. Accepted in International Work-Conference on Artificial and Natural Neural Networks (IWANN). Malaga (Spain, 2011), PP. 41-48.
55 Alfaro, R., Allende, H. (2011) Text Representation in Multi-label Classification: Two New Input Representations, 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part II, pp. 61-70.
56 vila, J.L., Gibaja, E.L., Zafra, A., Ventura, S. (2011) A gene expression programming algorithm for multi-label classification, Journal of Multiple-Valued Logic and Soft Computing, 17 (2-3), pp. 183-206.
57 Everton Alvares Cherman, Jean Metz, Maria Carolina Monard, (2011) Incorporating label dependency into the binary relevance framework for multi-label classification, Expert Systems with Applications, Available online 13 July 2011, ISSN 0957-4174,
58 Lastra, G., Luaces, O., Quevedo, J.R., Bahamonde, A. (2011) Graphical feature selection for multilabel classification tasks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7014 LNCS, pp. 246-257.
59 Vogrincic, S., Bosnic, Z. (2011) Ontology-based multi-label classification of economic articles, Computer Science and Information Systems, 8(1)
60 Jung-Yi Jiang, Ren-Jia Liou, and Shie-Jue Lee (2011) A Fuzzy Self-Constructing Feature Clustering Algorithm for Text Classification, IEEE TKDE 23(3), pp 335-349.
61 Bi, W., Kwok, J.T. (2011) Multi-label classification on tree- and DAG-structured hierarchies, Proceedings of the 28th International Conference on Machine Learning, ICML 2011, pp. 17-24.
62 Huang, K.-W., Li, Z. (2011) A multilabel text classification algorithm for labeling risk factors in sec form 10-K, ACM Transactions on Management Information Systems, 2 (3), art. no. 18.
63 Birzniece, I. (2011) Interactive inductive learning based classification system, Proceedings of the IADIS International Conference Intelligent Systems and Agents 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011, pp. 112-116.
64 Birzniece, I., Rudzajs, P. (2011) Machine learning based study course comparison, Proceedings of the IADIS International Conference Intelligent Systems and Agents 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011, pp. 107-111.
65 Zhang, Y., Schneider, J.(2011) Multi-label output codes using canonical correlation analysis, Journal of Machine Learning Research, 15, pp. 873-882.
66 Khlwein, D., Urban, J., Tsivtsivadze, E., Geuvers, H., Heskes, T. (2011) Multi-output ranking for automated reasoning, KDIR 2011 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, pp. 42-51.
67 Ulanov, A., Sapozhnikov, G., Lyubomishchenko, N., Shevlyakov, G. (2011) Enhancing Accuracy of Multilabel Classification by Extracting Hierarchies from Flat Clusterings, Proc. 8th International Workshop on Text-based Information Retrieval.
68 Petterson, J., Caetano, T. (2011) Submodular multi-label learning, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011
69 France, S.L., Abbasi, A. (2011) Boosting unsupervised additive clustering using cluster-wise optimization and multi-label learning, Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 6137385, pp. 236-243.
70 Chekina, L., Rokach, L., Shapira, B. (2011) Meta-learning for selecting a multi-label classification algorithm, Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 6137383, pp. 220-227.
71 Hospedales, T.M., Gong, S., Xiang, T. (2011) Learning tags from unsegmented videos of multiple human actions, Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 6137229, pp. 251-259.
72 Vens, C., Costa, F. (2011) Random forest based feature induction, Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 6137279, pp. 744-753.
73 Qu, G., Zhang, H., Hartrick, C.T. (2011) Multi-label classification with Bayes' theorem, Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011, 4, art. no. 6098780, pp. 2281-2285.
74 Joshi, S., Nigam, B. (2011) Categorizing the document using multi class classification in data mining, Proceedings - 2011 International Conference on Computational Intelligence and Communication Systems, CICN 2011, art. no. 6112865, pp. 251-255.
75 Wang, X., Li, G.-Z., Liu, J.-M., Zhao, R.-W. (2011) Multi-label learning for protein subcellular location prediction, Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011, art. no. 6120452, pp. 282-285.
76 Michael I. Mandel, Razvan Pascanu, Douglas Eck, Yoshua Bengio, Luca M. Aiello, Rossano Schifanella, and Filippo Menczer (2011) Contextual tag inference. ACM Trans. Multimedia Comput. Commun. Appl. 7S, 1, Article 32 (November 2011), 18 pages.
77 Sajnani, H., Javanmardi, S., McDonald, D.W., Lopes, C.V. (2011) Multi-label classification of short text: A study on Wikipedia barnstars, AAAI Workshop - Technical Report, WS-11-05, pp. 56-61.
78 Jean Metz, J., Freitas, A.A., Monard, M.C., Cherman, E.A. (2011) A study on the selection of local training sets for hierarchical classification tasks, Proc. ENIA 2011.
79 Wu, H., Qu, G., Zhang, H., Hartric, C. (2011) Constrained Multi-Label Classification: A Semidefinite Programming Approach, Proc. the 2011 International Conference on Data Mining, DMIN'11,
80 Costa, N., Coelho, A.L.V. (2011) Genetic and ranking-based selection of components for multilabel classifier ensembles, Hybrid Intelligent Systems (HIS), 2011 11th International Conference on , vol., no., pp.311-317, 5-8 Dec. 2011
81 Pillai, I., Fumera, F., Roli, F. (2011) Classifier Selection Approaches for Multi-label Problems, Proc. 10th International Workshop on Multiple Classifier Systems, MCS 2011, Naples, Italy, June 15-17, pp. 167-176.
82 Arunadevi, J., Rajamani, V. (2011) An evolutionary multi label classification using associative rule mining, International Journal of Soft Computing, 6 (2), pp. 20-25.
83 Xu, J. (2011) An Empirical Comparison of Weighting Functions for Multi-Label Distance Weighted K-Neared Neighbour Method, David Bracewell, et al. (Eds): AIAA 2011,CS and IT 03, pp. 1320, 2011.
84 Cerri, R., de Carvalho, A.C.P.L.F., Freitas, A.A. (2011) Adapting non-hierarchical multilabel classification methods for hierarchical multilabel classification, Intelligent Data Analysis, 16(5), pp. 861-887.
85 Fu, Z., Lu, G., Ting, K.-M., Zhang, D. (2011) On low-rank regularized least squares for scalable nonlinear classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7063 LNCS (PART 2), pp. 490-499.
86 Sanden, C., Zhang, J.Z. (2011) Enhancing multi-label music genre classification through ensemble techniques, SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 705-714.
87 Wang, C., Zheng, W., Liu, Z., Bai, Y., Wang, J. (2011) Using random walks for multi-label classification, International Conference on Information and Knowledge Management, Proceedings, pp. 2197-2200.
88 Ahmadi Abhari, K., Hamzeh, A., Hashemi, S. (2011) Voting based learning classifier system for multi-label classification, Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication, pp. 355-359
89 Xia, X., Yang, X., Li, S., Wu, C., Zhou, L. (2011) RW.KNN: A proposed random walk KNN algorithm for multi-label classification, International Conference on Information and Knowledge Management, Proceedings, pp. 87-90.
90 Ogrodniczuk, M., Karagiozov, D. (2011) ATLAS - The multilingual language processing platform, Procesamiento de Lenguaje Natural, 47, pp. 241-248.
91 Zhou, T., Tao, D. (2012) Labelset anchored subspace ensemble (LASE) for multi-label annotation, Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, ICMR 2012.
92 Birzniece, I. (2012) Interactive use of inductive approach for analyzing and developing conceptual structures, Proceedings - International Conference on Research Challenges in Information Science, art. no. 6240453
93 You, M., Liu, J., Li, G.-Z., Chen, Y. (2012) Embedded Feature Selection for Multi-label Classification of Music Emotions, International Journal of Computational Intelligence Systems, 5 (4), pp. 668-678.
94 Galbrun, E., Miettinen, P. (2012) From black and white to full color: Extending redescription mining outside the Boolean world, Statistical Analysis and Data Mining, 5 (4), pp. 284-303.
95 Santos, A.M., Canuto, A.M.P. (2012) Using semi-supervised learning in multi-label classification problems, Proceedings of the International Joint Conference on Neural Networks, art. no. 625280.
96 Gomez, J.C., Moens, M.-F. (2012) Hierarchical classification of web documents by stratified discriminant analysis, Proc. 5th Information Retrieval Facility Conference, IRFC 2012, 7356 LNCS, pp. 94-108.
97 Rubin, T.N., Chambers, A., Smyth, P., Steyvers, M. (2012) Statistical topic models for multi-label document classification, Machine Learning, 88 (1-2), pp. 157-208.
98 Zhang, S., Zhang, H. (2012) HDML: An approach to high-dimensional and multi-label classification, Journal of Computational Information Systems, 8 (13), pp. 5599-5606.
99 Dembczynski, K., Waegeman, W., Cheng, W., Hllermeier, E. (2012) On label dependence and loss minimization in multi-label classification, Machine Learning, 88 (1-2), pp. 5-45.
100 Qu, G., Wu, H., Hartrick, C.T., Niu, J. (2012) Local analgesia adverse effects prediction using multi-label classification, Neurocomputing, 92, pp. 18-27.
101 Wang,P.;Zhang,P.;Guo,L. (2012) Mining Multi-label Data Streams Using Ensemble-based Active Learning, In Proceedings of the 2012 SIAM International Conference on Data Mining (SDM-12), pp. 1131-1140, Anaheim, California, USA.
102 De Ferrari,L.;Aitken,S.,van Hemert,J.;Goryanin,I. (2012) EnzML: multi-label prediction of enzyme classes using InterPro signatures, BMC Bioinformatics 2012 Apr 25;13:61.
103 Kumar,A.;Vembu,S.;Menon,A.;Elkan,C. (2012) Learning and Inference in Probabilistic Classifier Chains with Beam Search, Proceedings ECML PKDD 2012, pp. 665-680.
104 Jing Zhang; Weiwei Hu; (2012) Effective multi-modal multi-label learning for automatic image annotation, Proceedings 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp.1216-1220, 29-31 May 2012
105 Zhou, T., Tao, D., Wu, X. (2012) Compressed labeling on distilled labelsets for multi-label learning, Machine Learning, 88 (1-2), pp. 69-126.
106 Wang, X., Li, G.-Z. (2012) A multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteins, PLoS ONE, 7 (5), art. no. e36317, .
107 Xu, J. (2012) An efficient multi-label support vector machine with a zero label, Expert Systems with Applications, 39 (5), pp. 4796-4804.
108 Yang, Q., Shao, J., Scholz, M., Boehm, C., Plant, C. (2012) Multi-label classification models for sustainable flood retention basins, Environmental Modelling and Software, 32, pp. 27-36.
109 Lpez, V.F., De La Prieta, F., Ogihara, M., Wong, D.D. (2012) A model for multi-label classification and ranking of learning objects, Expert Systems with Applications, 39 (10), pp. 8878-8884.
110 Madjarov, G., Gjorgjevikj, D. (2012) Hybrid decision tree architecture utilizing local SVMs for multi-label classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7209 LNAI (PART 2), pp. 1-12.
111 Charte, F., Rivera, A., Del Jesus, M.J., Herrera, F. (2012) Improving multi-label classifiers via label reduction with association rules, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7209 LNAI (PART 2), pp. 188-199.
112 Nasierding, G.; Kouzani, A.Z.; (2012) "Comparative evaluation of multi-label classification methods, Proceedings 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp.679-683, 29-31 May 2012.
113 Ramn Quevedo, J., Luaces, O., Bahamonde, A. (2012) Multilabel classifiers with a probabilistic thresholding strategy, Pattern Recognition, 45 (2), pp. 876-883.
114 Pacharawongsakda, E., Theeramunkong, T. Towards more efficient multi-label classification using dependent and independent dual space reduction (2012), Proc. 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012, 7301 LNAI (PART 2), pp. 383-394.
115 Li, G.-Z., Yan, S.-X., You, M., Sun, S., Ou, A. (2012) Intelligent ZHENG classification of hypertension depending on ML-kNN and information fusion, Evidence-based Complementary and Alternative Medicine, 2012, art. no. 837245
116 Xia, X., Yang, X., Li, S., Wu, C. (2012) A Bayesian Network nearest k-labels method for Multi-label classification, Advances in Information Sciences and Service Sciences, 4 (8), pp. 27-36.
117 Madjarov, G., Kocev, D., Gjorgjevikj, D., Deroski, S. (2012) An extensive experimental comparison of methods for multi-label learning, Pattern Recognition, 45 (9), pp. 3084-3104.
118 Tahir, M.A., Kittler, J., Yan, F. Inverse random under sampling for class imbalance problem and its application to multi-label classification (2012) Pattern Recognition, 45 (10), pp. 3738-3750.
119 Tsamardinos, I., Triantafillou, S., Lagani, V. (2012) Towards integrative causal analysis of heterogeneous data sets and studies, Journal of Machine Learning Research, 13, pp. 1097-1157.
120 Zhang, J., Han, B., Wei, X., Tan, C., Chen, Y., Jiang, Y. (2012) A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands, PLoS ONE, 7 (6), art. no. e39076.
121 Miao, X., Rao, R.P.N. (2012) Fast structured prediction using large margin sigmoid belief networks, International Journal of Computer Vision, 99 (3), pp. 302-318.
122 Fu, B., Wang, Z., Pan, R., Xu, G., Dolog, P. (2012) Learning tree structure of label dependency for multi-label learning, Proc 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012, 7301 LNAI (PART 1), pp. 159-170.


MLKD Home ISKP Home