マルチラベルの手法の中でメジャーなもの、引用数が多いものの元論文です。細かい手法は mulanのドキュメント にあるかもしれません。deep-learningは除外。slideshareなどの資料は応用例が多く手法の解説が少なかったので省略。
ベースライン
k Nearest Neighbours multi-label classifier
Zhang, Min-Ling, and Zhi-Hua Zhou. "ML-KNN: A lazy learning approach to multi-label learning." Pattern recognition 40.7 (2007): 2038-2048.
Label Powerset
Label Powerset
Cherman, Everton Alvares, Maria Carolina Monard, and Jean Metz. "Multi-label problem transformation methods: a case study." CLEI Electronic Journal 14.1 (2011): 4-4.
Kernel collaborative label power set
Al-Maadeed, Somaya. "Kernel collaborative label power set system for multi-label classification." Qatar Foundation Annual Research Conference. No. 2013. 2013.
BinaryRelevance
Binary Relevance
ラベル間の関係が独立だと仮定しているBinary Relevanceは、通常この仮定がおかしいから〜と言われている。そのBinary Relevanceの性質の検証を行った論文。
Luaces, Oscar, et al. "Binary relevance efficacy for multilabel classification." Progress in Artificial Intelligence 1.4 (2012): 303-313.
Binary Relevance with K-NN
Spyromitros, Eleftherios, Grigorios Tsoumakas, and Ioannis Vlahavas. "An empirical study of lazy multilabel classification algorithms." Hellenic conference on artificial intelligence. Springer, Berlin, Heidelberg, 2008.
Stacked binary relevance
Tsoumakas, Grigorios, et al. "Correlation-based pruning of stacked binary relevance models for multi-label learning." Proceedings of the 1st international workshop on learning from multi-label data. 2009.
Random k-Labelsets
Distinct Random k-Labelsets
Overlaping Random k-Labelsets
Tsoumakas, Grigorios, Ioannis Katakis, and Ioannis Vlahavas. "Random k-labelsets for multilabel classification." IEEE Transactions on Knowledge and Data Engineering 23.7 (2011): 1079-1089.
Classifier Chains
Classifier Chains
Read, Jesse, et al. "Classifier chains for multi-label classification." Machine learning 85.3 (2011): 333-359.
Selective Ensemble of Classifier Chains
Li, Nan, and Zhi-Hua Zhou. "Selective ensemble of classifier chains." International Workshop on Multiple Classifier Systems. Springer, Berlin, Heidelberg, 2013.
Bayes Optimal Probabilistic Classifier Chains
Cheng, Weiwei, Eyke Hüllermeier, and Krzysztof J. Dembczynski. "Bayes optimal multilabel classification via probabilistic classifier chains." Proceedings of the 27th international conference on machine learning (ICML-10). 2010.
Genetic Algorithm for ordering Classifier Chains
Goncalves, Eduardo Corrêa, Alexandre Plastino, and Alex A. Freitas. "A genetic algorithm for optimizing the label ordering in multi-label classifier chains." Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on. IEEE, 2013.
その他
Hierarchical ARAM Neural Network
Tsoumakas, Grigorios, Ioannis Katakis, and Ioannis Vlahavas. "Effective and efficient multilabel classification in domains with large number of labels." Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD’08). 2008.
Calibrated Label Ranking
Fürnkranz, Johannes, et al. "Multilabel classification via calibrated label ranking." Machine learning 73.2 (2008): 133-153.
ライブラリ
Mulan: A java library for multi-label learning
ライブラリ公式：http://mulan.sourceforge.net/
Tsoumakas, Grigorios, et al. "Mulan: A java library for multi-label learning." Journal of Machine Learning Research 12.Jul (2011): 2411-2414.
…多い。
