LPIS Home Page
Google Search

Title: Multilabel Classification of Music into Emotions
Author(s): K. Trohidis, G. Tsoumakas, G. Kalliris, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (6 pages).
Appeared in: Proc. 9th International Conference on Music Information Retrieval (ISMIR 2008), pp. 325-330, Philadelphia, PA, USA, 2008.
Abstract: In this paper, the automated detection of emotion in music is modeled as a multilabel classification task, where a piece of music may belong to more than one class. Four algorithms are evaluated and compared in this task. Furthermore, the predictive power of several audio features is evaluated using a new multilabel feature selection method. Experiments are conducted on a set of 593 songs with 6 clusters of music emotions based on the Tellegen-Watson-Clark model. Results provide interesting insights into the quality of the discussed algorithms and features.
See also :

        This paper has been cited by the following:

1 Makoto P. Kato (2009) RHYTHMIXEARCH: SEARCHING FOR UNKNOWN MUSIC BY MIXING KNOWN MUSIC, 10th International Society for Music Information Retrieval Conference (ISMIR 2009).
2 Alluri, V., Toiviainen, P. (2009) In Search of Perceptual and Acoustical Correlates of Polyphonic Timbre. Proceedings of the 7th Triennial Conference of European Society for the Cognitive Sciences of Music (ESCOM 2009) Jyväskylä, Finland, pp. 5-10.
3 Brandenburg. K., Dittmar, C., Gruhne, M., Abeßer, J., Lukashevich, H., Dunker, P., Gärtner, D., Wolter, K. Grossmann, H., (2009) Music Search and Recommendation, Chapter in Handbook of Multimedia for Digital Entertainment and Arts, pp. 349-384.
4 Liu, Y., Gao, Y., (2009) "Acquiring Mood Information from Songs in Large Music Database," ncm, pp.1485-1491, 2009 Fifth International Joint Conference on INC, IMS and IDC.
5 W. Jiang, A. Cohen, Z.W. Ras, “Polyphonic Music Information Retrieval Based on Multi-label Cascade Classification System” in ”Advances in Information and Intelligent Systems”, Z.W. Ras, W. Ribarsky (Eds.), Studies in Computational Intelligence, Springer, 2009.
6 Hanna Lukashevich, Jakob Abeßer, Christian Dittmar, Holger Grossmann (2009) FROM MULTI-LABELING TO MULTI-DOMAIN-LABELING: A NOVEL TWO-DIMENSIONAL APPROACH TO MUSIC GENRECLASSIFICATION, 10th International Society for Music Information Retrieval Conference (ISMIR 2009).
7 Hoffman, M., D. Blei, and P.R. Cook "Easy as CBA: A Simple Probabilistic Model for Tagging Music," In Proceedings of the 10th International Conference on Music Information Retrieval, Kobe, 2009.
8 Sapozhnikova, E.P. (2009), “ART-Based Neural Networks for Multi-label Classification”, Proceedings of the 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, pp. 167-177.
9 Zhang, M.-L., Peña, J.M., Robles, V. "Feature selection for multi-label naive Bayes classification", Information Sciences, 179 (19) pp. 3218-3229, 2009.
10 Aiyesha Ma, Ishwar Sethi, Nilesh Patel, (2009) "Multimedia Content Tagging Using Multilabel Decision Tree", Proc. 11th IEEE International Symposium on Multimedia, pp. 606-611.
11 Ness, S. R., Theocharis, A., Tzanetakis, G., and Martins, L. G. 2009. Improving automatic music tag annotation using stacked generalization of probabilistic SVM outputs. In Proceedings of the Seventeen ACM international Conference on Multimedia (Beijing, China, October 19 - 24, 2009). MM '09. ACM, New York, NY, 705-708.
12 Younes, Z., Abdallah, F., Denoeux, T. (2009) An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification, Proc. 3rd International Conference on Scalable Uncertainty Management, SUM 2009, Washington, DC, USA, September 28-30, 2009, pp. 297-308.
13 Tenenboim, L., Rokach, L., Shapira, B. (2009) Multi-label Classification by Analyzing Labels Dependencies, Proceedings of the ECML/PKDD 2009 Workshop on Learning from Multi-Label Data (MLD’09), pp. 117-131, Bled, Slovenia, September 2009.
14 Cheng, W., Hüllermeier, E. (2009) A Simple Instance-Based Approach to Multilabel Classification Using the Mallows Model, Proceedings of the ECML/PKDD 2009 Workshop on Learning from Multi-Label Data (MLD’09), pp. 28-38, Bled, Slovenia, September 2009.
15 Read, J. Pfahringer, B., Holmes, G., Frank, E. (2009) Classifier chains for multi-label classification. In Proc 13th European Conference on Principles and Practice of Knowledge Discovery in Databases and 20th European Conference on Machine Learning, Bled, Slovenia. Springer, 2009, pp. 254-269.
16 Cheng, W., Hüllermeier, E. (2009) Combining instance-based learning and logistic regression for multilabel classification, Machine Learning, 76, 2-3 (September 2009), 211-225.
17 Burred, J.J.,Peeters, G. (2009) An Adaptive System for Music Classification and Tagging, Proc. 3rd International Workshop on Learning Semantics of Audio Signals, pp. 3-16.
18 Itach, E., Tenenboim, L., Rokach, L. (2009) An Ensemble Method for Multi-label Classification using a Transportation Model, Proceedings of the ECML/PKDD 2009 Workshop on Learning from Multi-Label Data (MLD’09), pp. 49-60, Bled, Slovenia, September 2009.
19 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 (MLD’09), pp. 146-160, Bled, Slovenia, September 2009.
20 Wang, H., Ding, C., Huang, H. (2010) Multi-label classification: Inconsistency and Class Balanced K-Nearest Neighbor, Proceedings of the National Conference on Artificial Intelligence, 2, pp. 1264-1266.
21 Hu, X. and Downie, J. S. (2010). Improving mood classification in music digital libraries by combining lyrics and audio. In Proceedings of the 10th Annual Joint Conference on Digital Libraries (Gold Coast, Queensland, Australia, June 21 - 25, 2010). JCDL '10. ACM, New York, NY, 159-168.
22 Law, E., Settles, B., Mitchell, T. (2010) Learning to Tag from Open Vocabulary Labels, Proc. ECML/PKDD 2010, pp. 211-226.
23 Lukashevich, H., Dittmar, C. (2010), Improving GMM Classifiers by Preliminary One-class SVM Outlier Detection: Application to Automatic Music Mood Estimation, Classification as a Tool for Research: Studies in Classification, Data Analysis, and Knowledge Organization, 2010, Part 3, 775-782.
24 Wang, H., Ding, C., Huang, H. (2010) Directed Graph Learning via High-Order Co-linkage Analysis, Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science, 2010, Volume 6323/2010, 451-466
25 Panagakis, Y., Kotropoulos, C., Arce, G. R. (2010) Sparse multi-label linear embedding within nonnegative tensor factorization applied to music tagging, Proc. 11th International Society for Music Information Retrieval Conference (ISMIR 2010), pp. 393 – 398.
26 Wang, H., Ding, C., Huang, H. (2010) Multi-label Linear Discriminant Analysis, Computer Vision – ECCV 2010, Lecture Notes in Computer Science, 2010, Volume 6316/2010, 126-139
27 Gopal, S. and Yang, Y. 2010. Multilabel classification with meta-level features. In Proceeding of the 33rd international ACM SIGIR Conference on Research and Development in information Retrieval (Geneva, Switzerland, July 19 - 23, 2010). SIGIR '10. ACM, New York, NY, 315-322.
28 Oliveira, A. P. and Cardoso, A. (2010). A musical system for emotional expression. Know.-Based Syst. 23(8), pp. 901-913.
29 Denoeux, T., Younes, Z., and Abdallah, F. (2010). Representing uncertainty on set-valued variables using belief functions. Artif. Intell. 174, 7-8 (May. 2010)
30 Wang, H., Ding, C., Huang, H. (2010) Multi-label classification: Inconsistency and Class Balanced K-Nearest Neighbor, Proceedings of the National Conference on Artificial Intelligence, 2, pp. 1264-1266.
31 Wang, H., Huang, H., Ding, C. (2010) Discriminant laplacian embedding (2010) Proceedings of the National Conference on Artificial Intelligence, 1, pp. 618-623.
32 Huq, A., Bello, J.P., Rowe, R.(2010) Automated music emotion recognition: A systematic evaluation, Journal of New Music Research, 39 (3), pp. 227-244.
33 Madjarov, G., Gjorgjevikj, G.D., Delev, T. (2010) Efficient Two Stage Voting Architecture for Pairwise Multi-label Classification, Proc. 23rd Australasian Joint Conference on Advances in Artificial Intelligence, AI 2010, Adelaide, Australia, December 7-10, 2010, pp. 164-173.
34 Benhui Chen; Weifeng Gu; Jinglu Hu; , "An improved multi-label classification based on label ranking and delicate boundary SVM," Neural Networks (IJCNN), The 2010 International Joint Conference on , vol., no., pp.1-6, 18-23 July 2010
35 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.
36 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.
37 Austin, A., Moore, E., Gupta, U., Chordia, P. (2010) Characterization of movie genre based on music score, Proc. 2010 IEEE Int. Conf. on Acoustics Speech and Signal Processing (ICASSP), 14-19 March 2010, pp 421 – 424, Dallas, TX, USA
38 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
39 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.
40 Correa, D.C., Saito J.H., da Costa, L.F. (2010) Musical genres: beating to the rhythms of different drums. New Journal of Physics 12.
41 Kuang, Q., Xu, X. (2010) Improvement and Application of TF•IDF Method Based on Text Classification, Proc. Int. Conf. on Internet Technology and Applications, 2010, Wuhan, China, 20-22 Aug. 2010. pp. 1-4.
42 Chen, B., Gu, W., Hu, J. (2010) An improved multi-label classification method and its application to functional genomics, International Journal of Computational Biology and Drug Design, 3 (2), pp. 133-145.
43 Younes, Z.; Abdallah, F.; Denœux, T.; , "Fuzzy multi-label learning under veristic variables," Fuzzy Systems (FUZZ), 2010 IEEE International Conference on , vol., no., pp.1-8, 18-23 July 2010
44 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.
45 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.
46 Schuller, B., Hagel, C., Schuller, D., Rigoll, G. (2010) 'Mister D.j., Cheer me Up!': Musical and textual features for automatic mood classification, Journal of New Music Research, 39 (1), pp. 13-34.
47 Read, J. (2010) Scalable Multi-Label Classification, PhD Thesis, University of Waikato.
48 Denoeux, T., Masson, M.-H. (2010) Dempster-Shafer reasoning in large partially ordered sets: Applications in Machine Learning, Proc. Workshop on the Theory of Belief Functions.
49 Michael Stein, M. (2010) Automatic Detection of Multiple, Cascased Audio Effects in Guitar Recordings, Proc. of the 13th Int. Conference on Digital Audio Effects (DAFx-10), Graz, Austria , September 6-10, 2010
50 Tai, F, Lin H.-T. (2010) Multi-Label Classification with Principle Label Space Transformation, Proc. 2nd International Workshop on Multi-Label Learning.
51 Duivesteijn, W., Knobbe, A., Feelders, A., Van Leeuwen, M. (2010) Subgroup discovery meets Bayesian networks - An Exceptional Model Mining approach (2010) Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 5693969, pp. 158-167.
52 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.
53 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.
54 Björn Schuller, Johannes Dorfner, and Gerhard Rigoll, “Determination of Nonprototypical Valence and Arousal in Popular Music: Features and Performances,” EURASIP Journal on Audio, Speech, and Music Processing, vol. 2010, Article ID 735854, 19 pages, 2010.
55 Hu, X. (2010) IMPROVING MUSIC MOOD CLASSIFICATION USING LYRICS, AUDIO AND SOCIAL TAGS, PhD Thesis, University of Illinois at Urbana-Champaign.
56 Cheng, W, Dembczynski, K. Hullermeier, E. (2010) Graded Multilabel Classification: The Ordinal Case, Proc. Proceedings of the 27 th International Conference on Machine Learning, Haifa, Israel, 2010.
57 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.
58 Li, Y., Yang, S., Li, W., Zhu, Y. (2010) Music emotion detecting based on beat spectrum, Proceedings - 2010 International Conference on Computational and Information Sciences, ICCIS 2010, art. no. 5709507, pp. 1245-1248.
59 Lu, C.-C., Tseng, V.S. (2010) A novel method for music retrieval by integrating content-based and emotion-based features, International Journal of Innovative Computing, Information and Control, 6 (9), pp. 4077-4091.
60 Bertin-Mahieux, T., Eck, D., Mandel, M. (2010) Automatic tagging of audio: The state-of-the-art. In Wenwu Wang, editor, Machine Audition: Principles, Algorithms and Systems. IGI Publishing, 2010
61 Hu, X., Downie, J.S. (2010) When Lyrics Outperform Audio for Music Mood Classification: A Feature Analysis, Proc. ISMIR 2010, pp. 619-624.
62 Bindoff, I. (2010) Multiple classification ripple round rules: classifications as conditions. PhD Thesis, University of Tasmania.
63 Cheng, W., Dembczynski, K., Hüllermeier, E. (2010) Proceedings of the LWA 2010: Lernen, Wissen and Adaptivität, Workshop on Knowledge Discovery and Machine Learning (KDML 2010)
64 Kazienko, P., Kajdanowicz, T. (2010) Base classifiers in boosting-based classification of sequential structures, Neural Network World, 20 (7), pp. 839-851.
65 Y.Panagakis, C.Kotropoulos and G.R.Arce, "Sparse multi-label linear embedding nonnegative tensor factorization for automatic music tagging" in Proc. 2010 European Signal Processing Conf., Aalborg, Denmark, pp. 492-496, August, 2010.
66 MacHot, F.A., Mosa, A.H., Fasih, A., Schwarzlmüller, C., Ali, M., Kyamakya, K. (2011) A novel real-time emotion detection system for advanced driver assistance systems, Studies in Computational Intelligence, 391, pp. 267-276.
67 Kuang, Q., Xu, X. (2011) An improved feature weighting method for text classification, Advances in Information Sciences and Service Sciences, 3 (7), pp. 340-346.
68 Al Machot, F., Mosa, A.H., Dabbour, K., Fasih, A., Schwarzlmüller, C., Ali, M., Kyamakya, K. (2011) A novel real-time emotion detection system from audio streams based on Bayesian Quadratic Discriminate Classifier for ADAS, Proceedings of the Joint 3rd International Workshop on Nonlinear Dynamics and Synchronization, INDS'11 and 16th International Symposium on Theoretical Electrical Engineering, ISTET'11, art. no. 6024783, pp. 47-51.
69 Kajdanowicz, T., Kazienko, P.L. (2011) Boosting-based sequential output prediction, New Generation Computing, 29 (3), pp. 293-307.
70 Guan, Y., Zhou, C. (2011) Machine transcription of guqin tablature and automatic music rhythm tagging, Journal of Information and Computational Science, 8 (11), pp. 2164-2176.
71 Ávila, 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.
72 Gjorgjevikj, D., Madjarov, G. (2011) Two stage classifier chain architecture for efficient pair-wise multi-label learning, IEEE International Workshop on Machine Learning for Signal Processing, art. no. 6064599, .
73 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.
74 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.
75 Sanden, C., Zhang, J. (2011) An Empirical Study of Multi-Label Classifiers for Music Tag Annotation, Proc. 12th International Society for Music Information Retrieval Conference, ISMIR'11, October 24-28, pp. 717-722
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 Panagakis, Y., Kotropoulos, C. (2011) Automatic music mood classification via low-rank representation, European Signal Processing Conference, pp. 689-693.
78 Lin, Y.-C., Yang, Y.-H., Chen, H.H. (2011) Exploiting online music tags for music emotion classification, ACM Transactions on Multimedia Computing, Communications and Applications, 7 S (1), art. no. 26
79 Catal, C. (2011) Software fault prediction: A literature review and current trends, Expert Systems with Applications, 38 (4), pp. 4626-4636.
80 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
81 Miyoshi, Masato; Tsuge, Satoru; Oyama, Tadahiro; Ito, Momoyo; Fukumi, Minoru; , "Feature selection method for music mood score detection," Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on , vol., no., pp.1-6, 19-21 April 2011
82 Yi-Hsuan Yang; Chen, H.H.; , "Prediction of the Distribution of Perceived Music Emotions Using Discrete Samples," Audio, Speech, and Language Processing, IEEE Transactions on , vol.19, no.7, pp.2184-2196, Sept. 2011
83 Kajdanowicz, T., Wozniak, M., Kazienko, P. (2011) Multiple Classifier Method for Structured Output Prediction Based on Error Correcting Output Codes, Proceedings, Part II, 3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011, Daegu, Korea, April 20-22, 2011, pp. 333-342.
84 Bielza, C., Li, G., Larrañaga, P. Multi-dimensional classification with Bayesian networks (2011) International Journal of Approximate Reasoning, 52 (6), pp. 705-727.
85 Fu, Z., Lu, G., Ting, K. M., Zhang, D. (2011) "A Survey of Audio-based Music Classification and Annotation," Multimedia, IEEE Transactions on , vol.PP, no.99, pp.1, 0
86 Doquire, G., Verleysen, M. (2011) Feature Selection for Multi-label Classification Problems, Proceedings, Part I, 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, pp. 9-16.
87 Agovic, A., Banerjee, A., Chatterjee, S. (2011) Probabilistic matrix addition, Proceedings of the 28th International Conference on Machine Learning, ICML 2011, pp. 1025-1032.
88 Vivian F. López Batista, Fernando Prieta Pintado, Ana Belén Gil, Sara Rodríguez and María 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.
89 Cherman, E.A., Metz, J., Monard, M.C. (2011) Multi-label Problem Transformation Methods: a Case Study, CLEI Electronic Journal, 14(1), paper 4.
90 Yuki Ichiyanagi, Eric W. Cooper, Victor V. Kryssanov and Hitoshi Ogawa (2011) A Haptic Emotional Model for Audio System Interface, In Human-Computer Interaction: Towards Mobile and Intelligent Interaction Environments, pp. 535-542
91 Younes, Z., Abdallah, F., Denoeux, T., Snoussi, H. (2011) A dependent multilabel classification method derived from the k-nearest neighbor rule, Eurasip Journal on Advances in Signal Processing, art. no. 645964,
92 Hüllermeier, E., Schlegel, P.(2011) Preference-Based CBR: First Steps Toward a Methodological Framework. Proc. ICCBR-2011, 19th International Conference on Case-Based Reasoning, London, September 2011, pp. 77-91
93 Xu, J. (2011) An extended one-versus-rest support vector machine for multi-label classification, Neurocomputing, 74 (17), pp. 3114-3124.
94 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,
95 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.
96 Yang, Y., Chen, H. (2011) Ranking-Based Emotion Recognition for Music Organization and Retrieval, IEEE Transactions on Audio, Speech, and Language Processing 19(4), pp. 762-774.
97 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.
98 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.
99 Yang, Y.-H., Chen, H.H. (2012) Machine recognition of music emotion: A review, ACM Transactions on Intelligent Systems and Technology, 3 (3), art. no. 40
100 Zhou, T., Tao, D., Wu, X. (2012) Compressed labeling on distilled labelsets for multi-label learning, Machine Learning, 88 (1-2), pp. 69-126.
101 Dembczynski, K., Waegeman, W., Cheng, W., Hüllermeier, E. (2012) On label dependence and loss minimization in multi-label classification, Machine Learning, 88 (1-2), pp. 5-45.
102 Cesa-Bianchi, N., Re, M., Valentini, G. (2012) Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference, Machine Learning, 88 (1-2), pp. 209-241.
103 Yang, Y., Gopal, S. (2012) Multilabel classification with meta-ievel features in a iearning-to-rank framework, Machine Learning, 88 (1-2), pp. 47-68.
104 Lee,J.;Lim,H.;Kim,D.-W.; (2012) Approximating mutual information for multi-label feature selection, Electronics Letters , vol.48, no.15, pp.929-930, July 19 2012
105 Kanj, S., Abdallah, F., Denœux, T. (2012) Evidential multi-label classification using the random k-label sets approach, Advances in Intelligent and Soft Computing, 164 AISC, pp. 21-28.
106 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.
107 Wicker, J., Pfahringer, B., Kramer, S. (2012) Multi-label classification using boolean matrix decomposition, Proceedings of the ACM Symposium on Applied Computing, pp. 179-186.
108 Ying, T.C., Doraisamy, S., Abdullah, L.N. (2012) Genre and mood classification using lyric features, Proceedings - 2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12, art. no. 6204985, pp. 260-263.
109 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.
110 Gjorgji Madjarov, Dejan Gjorgjevikj, Sašo Džeroski (2012) Two stage architecture for multi-label learning, Pattern Recognition, Volume 45, Issue 3, March 2012, Pages 1019-1034, ISSN 0031-3203
111 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.
112 Khair, N.M., Yaacob, S., Hariharan, M., Basah, S.N. (2012) A study of human emotional: Review, 2012 International Conference on Biomedical Engineering, ICoBE 2012, art. no. 6179045, pp. 393-399.
113 López, 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.
114 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.
115 Xu, J. (2012) An efficient multi-label support vector machine with a zero label, Expert Systems with Applications, 39 (5), pp. 4796-4804.
116 Madjarov, G., Kocev, D., Gjorgjevikj, D., Džeroski, S. (2012) An extensive experimental comparison of methods for multi-label learning, Pattern Recognition, 45 (9), pp. 3084-3104.