-
1
-
-
0033905095
-
BoosTexter: A boosting-based system for text categorization
-
R. Schapire and Y. Singer, "BoosTexter: A boosting-based system for text categorization," Mach. Learn., vol. 39, no. 2, pp. 135-168, 2000.
-
(2000)
Mach. Learn.
, vol.39
, Issue.2
, pp. 135-168
-
-
Schapire, R.1
Singer, Y.2
-
2
-
-
70349494362
-
Learning multi-label alternating decision trees from texts and data
-
F. De Comité, R. Gilleron, and M. Tommasi, "Learning multi-label alternating decision trees from texts and data," in Proc. 3rd Int. Conf. MLDM Pattern Recognit., 2003, pp. 251-274.
-
(2003)
Proc. 3rd Int. Conf. MLDM Pattern Recognit.
, pp. 251-274
-
-
De Comité, F.1
Gilleron, R.2
Tommasi, M.3
-
3
-
-
84899033524
-
Maximal margin labeling for multi-topic text categorization
-
H. Kazawa, T. Izumitani, H. Taira, and E. Maeda, "Maximal margin labeling for multi-topic text categorization," in Proc. Adv. NIPS, vol. 17. 2005, pp. 649-656.
-
(2005)
Proc. Adv. NIPS
, vol.17
, pp. 649-656
-
-
Kazawa, H.1
Izumitani, T.2
Taira, H.3
Maeda, E.4
-
4
-
-
84898954552
-
Parametric mixture models for multi-labeled text
-
N. Ueda and K. Saito, "Parametric mixture models for multi-labeled text," in Proc. Adv. NIPS, vol. 15. 2003, pp. 721-728.
-
(2003)
Proc. Adv. NIPS
, vol.15
, pp. 721-728
-
-
Ueda, N.1
Saito, K.2
-
5
-
-
76649137444
-
A kernel method for multi-labelled classification
-
A. Elisseeff and J. Weston, "A kernel method for multi-labelled classification," in Proc. Adv. NIPS, vol. 14. 2002, pp. 681-687.
-
(2002)
Proc. Adv. NIPS
, vol.14
, pp. 681-687
-
-
Elisseeff, A.1
Weston, J.2
-
6
-
-
33748366796
-
Multilabel neural networks with applications to functional genomics and text categorization
-
Oct.
-
M. Zhang and Z. Zhou, "Multilabel neural networks with applications to functional genomics and text categorization," IEEE Trans. Knowl. Data Eng., vol. 18, no. 10, pp. 1338-1351, Oct. 2006.
-
(2006)
IEEE Trans. Knowl. Data Eng.
, vol.18
, Issue.10
, pp. 1338-1351
-
-
Zhang, M.1
Zhou, Z.2
-
8
-
-
3042597440
-
Learning multi-label scene classification
-
M. Boutell, J. Luo, X. Shen, and C. Brown, "Learning multi-label scene classification," Pattern Recognit., vol. 37, no. 9, pp. 1757-1771, 2004.
-
(2004)
Pattern Recognit.
, vol.37
, Issue.9
, pp. 1757-1771
-
-
Boutell, M.1
Luo, J.2
Shen, X.3
Brown, C.4
-
9
-
-
33947681316
-
ML-KNN: A lazy learning approach to multi-label learning
-
M. Zhang and Z. Zhou, "ML-KNN: A lazy learning approach to multi-label learning," Pattern Recognit., vol. 40, no. 7, pp. 2038-2048, 2007.
-
(2007)
Pattern Recognit.
, vol.40
, Issue.7
, pp. 2038-2048
-
-
Zhang, M.1
Zhou, Z.2
-
10
-
-
37849015906
-
Correlative multi-label video annotation
-
G. Qi, X. Hua, Y. Rui, J. Tang, T. Mei, and H. Zhang, "Correlative multi-label video annotation," in Proc. 15th Int. Conf. Multimedia, 2007, pp. 17-26.
-
(2007)
Proc. 15th Int. Conf. Multimedia
, pp. 17-26
-
-
Qi, G.1
Hua, X.2
Rui, Y.3
Tang, J.4
Mei, T.5
Zhang, H.6
-
11
-
-
84873447495
-
Multilabel classification of music into emotions
-
K. Trohidis, G. Tsoumakas, G. Kalliris, and I. Vlahavas, "Multilabel classification of music into emotions," in Proc. 9th Int. Conf. Music Inf. Retrieval, 2008, pp. 325-330.
-
(2008)
Proc. 9th Int. Conf. Music Inf. Retrieval
, pp. 325-330
-
-
Trohidis, K.1
Tsoumakas, G.2
Kalliris, G.3
Vlahavas, I.4
-
12
-
-
34748873053
-
Multi-label classification: An overview
-
G. Tsoumakas and I. Katakis, "Multi-label classification: An overview," Int. J. Data Warehousing, Mining, vol. 3, no. 3, pp. 1-13, 2007.
-
(2007)
Int. J. Data Warehousing, Mining
, vol.3
, Issue.3
, pp. 1-13
-
-
Tsoumakas, G.1
Katakis, I.2
-
13
-
-
77956163078
-
Mining multi-label data
-
New York, NY, USA: Springer-Verlag
-
G. Tsoumakas, I. Katakis, and I. Vlahavas, "Mining multi-label data," in Data Mining and Knowledge Discovery Handbook. New York, NY, USA: Springer-Verlag, 2010, pp. 667-685.
-
(2010)
Data Mining and Knowledge Discovery Handbook
, pp. 667-685
-
-
Tsoumakas, G.1
Katakis, I.2
Vlahavas, I.3
-
15
-
-
84885572482
-
Multi-labelled classification using maximum entropy method
-
S. Zhu, X. Ji, W. Xu, and Y. Gong, "Multi-labelled classification using maximum entropy method," in Proc. 28th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2005, pp. 274-281.
-
(2005)
Proc. 28th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval
, pp. 274-281
-
-
Zhu, S.1
Ji, X.2
Xu, W.3
Gong, Y.4
-
17
-
-
78149274348
-
Using information gain to build meaningful decision forests for multilabel classification
-
Jan.
-
K. Gold and A. Petrosino, "Using information gain to build meaningful decision forests for multilabel classification," in Proc. IEEE 9th Int. Conf. Develop. Learn., Jan. 2010, pp. 58-63.
-
(2010)
Proc. IEEE 9th Int. Conf. Develop. Learn.
, pp. 58-63
-
-
Gold, K.1
Petrosino, A.2
-
18
-
-
68949141664
-
Combining instance-based learning and logistic regression for multilabel classification
-
W. Cheng and E. Hüllermeier, "Combining instance-based learning and logistic regression for multilabel classification," Mach. Learn., vol. 76, no. 2, pp. 211-225, 2009.
-
(2009)
Mach. Learn.
, vol.76
, Issue.2
, pp. 211-225
-
-
Cheng, W.1
Hüllermeier, E.2
-
19
-
-
0002343269
-
Top-down induction of clustering trees
-
H. Blockeel, L. D. Raedt, and J. Ramon, "Top-down induction of clustering trees," in Proc. 15th Int. Conf. Mach. Learn., 2000, pp. 55-63.
-
(2000)
Proc. 15th Int. Conf. Mach. Learn.
, pp. 55-63
-
-
Blockeel, H.1
Raedt, L.D.2
Ramon, J.3
-
20
-
-
52949141834
-
Decision trees for hierarchical multi-label classification
-
C. Vens, J. Struyf, L. Schietgat, S. Džeroski, and H. Blockeel, "Decision trees for hierarchical multi-label classification," Mach. Learn., vol. 73, no. 2, pp. 185-214, 2008.
-
(2008)
Mach. Learn.
, vol.73
, Issue.2
, pp. 185-214
-
-
Vens, C.1
Struyf, J.2
Schietgat, L.3
Džeroski, S.4
Blockeel, H.5
-
21
-
-
38049132551
-
Ensembles of multi-objective decision trees
-
D. Kocev, C. Vens, J. Struyf, and S. Džeroski, "Ensembles of multi-objective decision trees," in Proc. ECML, 2007, pp. 624-631.
-
(2007)
Proc. ECML
, pp. 624-631
-
-
Kocev, D.1
Vens, C.2
Struyf, J.3
Džeroski, S.4
-
22
-
-
21844440579
-
Core vector machines: Fast SVM training on very large datasets
-
I. W. Tsang, J. T. Kwok, and P. M. Cheung, "Core vector machines: Fast SVM training on very large datasets," J. Mach. Learn. Res., vol. 6, no. 1, pp. 363-392, 2006.
-
(2006)
J. Mach. Learn. Res.
, vol.6
, Issue.1
, pp. 363-392
-
-
Tsang, I.W.1
Kwok, J.T.2
Cheung, P.M.3
-
23
-
-
74849083829
-
Effective and efficient multilabel classification in domains with large number of labels
-
G. Tsoumakas, I. Katakis, and I. Vlahavas, "Effective and efficient multilabel classification in domains with large number of labels," in Proc. ECML/PKDD Workshop Mining Multidimensional Data, 2008, pp. 30-44.
-
(2008)
Proc. ECML/PKDD Workshop Mining Multidimensional Data
, pp. 30-44
-
-
Tsoumakas, G.1
Katakis, I.2
Vlahavas, I.3
-
24
-
-
85162050606
-
Label embedding trees for large multi-class tasks
-
S. Bengio, J. Weston, and D. Grangier, "Label embedding trees for large multi-class tasks," Adv. Neural Inf. Process. Syst., vol. 23, no. 1, pp. 163-171, 2010.
-
(2010)
Adv. Neural Inf. Process. Syst.
, vol.23
, Issue.1
, pp. 163-171
-
-
Bengio, S.1
Weston, J.2
Grangier, D.3
-
25
-
-
33749582181
-
Automatically learning document taxonomies for hierarchical classification
-
K. Punera, S. Rajan, and J. Ghosh, "Automatically learning document taxonomies for hierarchical classification," in Proc. Special Interest Tracks Posters 14th Int. Conf. World Wide Web, 2005, pp. 1010-1011.
-
(2005)
Proc. Special Interest Tracks Posters 14th Int. Conf. World Wide Web
, pp. 1010-1011
-
-
Punera, K.1
Rajan, S.2
Ghosh, J.3
-
26
-
-
85162353669
-
Fast and balanced: Efficient label tree learning for large scale object recognition
-
Dec.
-
J. Deng, S. Satheesh, A. Berg, and L. Fei-Fei, "Fast and balanced: Efficient label tree learning for large scale object recognition," Adv. Neural Inf. Process. Syst., vol. 2, pp. 567-575, Dec. 2011.
-
(2011)
Adv. Neural Inf. Process. Syst.
, vol.2
, pp. 567-575
-
-
Deng, J.1
Satheesh, S.2
Berg, A.3
Fei-Fei, L.4
-
27
-
-
84858821575
-
Hybrid decision tree architecture utilizing local SVMs for multi-label classification
-
G. Madjarov and D. Gjorgjevikj, "Hybrid decision tree architecture utilizing local SVMs for multi-label classification," in Proc. 7th Int. Conf. Hybrid Artif. Intell. Syst., 2012, pp. 1-12.
-
(2012)
Proc. 7th Int. Conf. Hybrid Artif. Intell. Syst.
, pp. 1-12
-
-
Madjarov, G.1
Gjorgjevikj, D.2
-
28
-
-
84861423296
-
Learning tree structure of label dependency for multi-label learning
-
B. Fu, Z. Wang, R. Pan, G. Xu, and P. Dolog, "Learning tree structure of label dependency for multi-label learning," in Proc. Adv. Knowl. Discovery Data Mining, 2012, pp. 159-170.
-
(2012)
Proc. Adv. Knowl. Discovery Data Mining
, pp. 159-170
-
-
Fu, B.1
Wang, Z.2
Pan, R.3
Xu, G.4
Dolog, P.5
-
29
-
-
34250747451
-
Hierarchical classification: Combining Bayes with SVM
-
N. Cesa-Bianchi, C. Gentile, and L. Zaniboni, "Hierarchical classification: Combining Bayes with SVM," in Proc. 23rd Int. Conf. Mach. Learn., 2006, pp. 177-184.
-
(2006)
Proc. 23rd Int. Conf. Mach. Learn.
, pp. 177-184
-
-
Cesa-Bianchi, N.1
Gentile, C.2
Zaniboni, L.3
-
30
-
-
33749236186
-
Incremental algorithms for hierarchical classification
-
N. Cesa-Bianchi, C. Gentile, A. Tironi, and L. Zaniboni, "Incremental algorithms for hierarchical classification," Adv. Neural Inf. Process. Syst., vol. 7, no. 1, pp. 233-240, 2005.
-
(2005)
Adv. Neural Inf. Process. Syst.
, vol.7
, Issue.1
, pp. 233-240
-
-
Cesa-Bianchi, N.1
Gentile, C.2
Tironi, A.3
Zaniboni, L.4
-
31
-
-
80053440655
-
Multi-label classification on tree- and DAG-structured hierarchies
-
W. Bi and J. T. Kwok, "Multi-label classification on tree- and DAG-structured hierarchies," in Proc. 28th ICML, 2011, pp. 17-24.
-
(2011)
Proc. 28th ICML
, pp. 17-24
-
-
Bi, W.1
Kwok, J.T.2
-
33
-
-
84861617363
-
An extensive experimental comparison of methods for multi-label learning
-
G. Madjarov, D. Kocev, D. Gjorgjevikj, and S. Džeroski, "An extensive experimental comparison of methods for multi-label learning," Pattern Recognit., vol. 45, no. 9, pp. 3084-3104, 2012.
-
(2012)
Pattern Recognit.
, vol.45
, Issue.9
, pp. 3084-3104
-
-
Madjarov, G.1
Kocev, D.2
Gjorgjevikj, D.3
Džeroski, S.4
-
34
-
-
83155175374
-
Classifier chains for multi-label classification
-
J. Read, B. Pfahringer, G. Holmes, and E. Frank, "Classifier chains for multi-label classification," Mach. Learn., vol. 85, no. 3, pp. 333-359, 2011.
-
(2011)
Mach. Learn.
, vol.85
, Issue.3
, pp. 333-359
-
-
Read, J.1
Pfahringer, B.2
Holmes, G.3
Frank, E.4
-
35
-
-
80052120667
-
Mulan: A Java library for multi-label learning
-
Jan.
-
G. Tsoumakas, J. Vilcek, L. Spyromitros, and I. Vlahavas, "Mulan: A Java library for multi-label learning," J. Mach. Learn. Res., vol. 1, pp. 1-48, Jan. 2010.
-
(2010)
J. Mach. Learn. Res.
, vol.1
, pp. 1-48
-
-
Tsoumakas, G.1
Vilcek, J.2
Spyromitros, L.3
Vlahavas, I.4
-
36
-
-
79955702502
-
LIBSVM: A library for support vector machines
-
C. Chang and C. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, p. 27, 2011.
-
(2011)
ACM Trans. Intell. Syst. Technol.
, vol.2
, Issue.3
, pp. 27
-
-
Chang, C.1
Lin, C.2
-
37
-
-
29644438050
-
Statistical comparisons of classifiers over multiple data sets
-
Jan.
-
J. Demšar, "Statistical comparisons of classifiers over multiple data sets," J. Mach. Learn. Res., vol. 7, pp. 1-30, Jan. 2006.
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 1-30
-
-
Demšar, J.1
-
38
-
-
78049326859
-
Regret analysis for performance metrics in multi-label classification: The case of Hamming and subset zero-one loss
-
K. Dembczyński, W. Waegeman, W. Cheng, and E. Hüllermeier, "Regret analysis for performance metrics in multi-label classification: The case of Hamming and subset zero-one loss," in Proc. Mach. Learn. Knowl. Discovery Databases, 2010, pp. 280-295.
-
(2010)
Proc. Mach. Learn. Knowl. Discovery Databases
, pp. 280-295
-
-
Dembczyński, K.1
Waegeman, W.2
Cheng, W.3
Hüllermeier, E.4
-
39
-
-
84866035306
-
Multi-label hypothesis reuse
-
S. Huang, Y. Yu, and Z. Zhou, "Multi-label hypothesis reuse," in Proc. 18th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2012, pp. 525-533.
-
(2012)
Proc. 18th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining
, pp. 525-533
-
-
Huang, S.1
Yu, Y.2
Zhou, Z.3
|