-
1
-
-
22944452794
-
Applying support vector machines to imbalanced datasets
-
Pisa, Italy, September 20–24, 2004. Proceedings, Springer, Berlin, pp 39–50
-
Akbani R, Kwek S, Japkowicz N (2004) Applying support vector machines to imbalanced datasets. In: Machine learning: ECML 2004: 15th European conference on machine learning, Pisa, Italy, September 20–24, 2004. Proceedings, Springer, Berlin, pp 39–50. doi:10.1007/978-3-540-30115-8_7
-
(2004)
In: Machine learning: ECML 2004: 15th European conference on machine learning
-
-
Akbani, R.1
Kwek, S.2
Japkowicz, N.3
-
5
-
-
0038209756
-
Benchmarking state-of-the-art classification algorithms for credit scoring
-
Baesens B, Van Gestel T, Viaene S, Stepanova M, Suykens J, Vanthienen J (2003) Benchmarking state-of-the-art classification algorithms for credit scoring. J Oper Res Soc 54(6):627–635. doi:10.1057/palgrave.jors.2601545
-
(2003)
J Oper Res Soc
, vol.54
, Issue.6
, pp. 627-635
-
-
Baesens, B.1
Van Gestel, T.2
Viaene, S.3
Stepanova, M.4
Suykens, J.5
Vanthienen, J.6
-
6
-
-
0036522693
-
Strategies for learning in class imbalance problems
-
Barandela R, Snchez J, Garca V, Rangel E (2003) Strategies for learning in class imbalance problems. Pattern Recognit 36(3):849–851. doi:10.1016/S0031-3203(02)00257-1
-
(2003)
Pattern Recognit
, vol.36
, Issue.3
, pp. 849-851
-
-
Barandela, R.1
Snchez, J.2
Garca, V.3
Rangel, E.4
-
7
-
-
37049032887
-
Modularity and community detection in bipartite networks
-
Barber MJ (2007) Modularity and community detection in bipartite networks. Phys Rev E 76(066):102. doi:10.1103/PhysRevE.76.066102
-
(2007)
Phys Rev E
, vol.76
, Issue.66
, pp. 102
-
-
Barber, M.J.1
-
8
-
-
84891807032
-
MWMOTE-majority weighted minority oversampling technique for imbalanced data set learning
-
Barua S, Islam MM, Yao X, Murase K (2014) MWMOTE-majority weighted minority oversampling technique for imbalanced data set learning. IEEE Trans Knowl Data Eng 26(2):405–425. doi:10.1109/TKDE.2012.232
-
(2014)
IEEE Trans Knowl Data Eng
, vol.26
, Issue.2
, pp. 405-425
-
-
Barua, S.1
Islam, M.M.2
Yao, X.3
Murase, K.4
-
9
-
-
27144531570
-
A study of the behavior of several methods for balancing machine learning training data
-
Batista GEAPA, Prati RC, Monard MC (2004) A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor Newsl 6(1):20–29. doi:10.1145/1007730.1007735
-
(2004)
SIGKDD Explor Newsl
, vol.6
, Issue.1
, pp. 20-29
-
-
Batista, G.E.A.P.A.1
Prati, R.C.2
Monard, M.C.3
-
10
-
-
84958068648
-
Improved community detection in weighted bipartite networks
-
Beckett SJ (2016) Improved community detection in weighted bipartite networks. R Soc Open Sci 3(1). doi:10.1098/rsos.140536
-
(2016)
R Soc Open Sci
, vol.3
, Issue.1
-
-
Beckett, S.J.1
-
11
-
-
84929326583
-
Evaluation measures for models assessment over imbalanced data sets
-
Bekkar M, Djemaa HK, Alitouche TA (2013) Evaluation measures for models assessment over imbalanced data sets. J Inf Eng Appl 3(10):27–38
-
(2013)
J Inf Eng Appl
, vol.3
, Issue.10
, pp. 27-38
-
-
Bekkar, M.1
Djemaa, H.K.2
Alitouche, T.A.3
-
12
-
-
78651086789
-
Data mining for credit card fraud: a comparative study
-
Bhattacharyya S, Jha S, Tharakunnel K, Westland JC (2011) Data mining for credit card fraud: a comparative study. Decis Support Syst 50(3):602–613. doi:10.1016/j.dss.2010.08.008
-
(2011)
Decis Support Syst
, vol.50
, Issue.3
, pp. 602-613
-
-
Bhattacharyya, S.1
Jha, S.2
Tharakunnel, K.3
Westland, J.C.4
-
13
-
-
56349094785
-
Fast unfolding of communities in large networks
-
Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theory Exp 10:P10,008
-
(2008)
J Stat Mech Theory Exp
, vol.10
, pp. P10,008
-
-
Blondel, V.D.1
Guillaume, J.L.2
Lambiotte, R.3
Lefebvre, E.4
-
15
-
-
70449521414
-
Recommender system for online dating service
-
In:, Conference, VSB, Ostrava
-
Brozovsky L, Petricek V (2007) Recommender system for online dating service. In: Proceedings of Znalosti 2007 Conference, VSB, Ostrava
-
(2007)
Proceedings of Znalosti
, pp. 2007
-
-
Brozovsky, L.1
Petricek, V.2
-
16
-
-
84865652746
-
-
Cha M, Mislove A, Gummadi KP (2009) A measurement-driven analysis of information propagation in the Flickr social network. In: Proceedings of the 18th international conference on world wide web, ACM, New York. WWW ’09, pp 721–730. doi:10.1145/1526709.1526806
-
(2009)
A measurement-driven analysis of information propagation in the Flickr social network. In: Proceedings of the 18th international conference on world wide web, ACM, New York. WWW ’09, pp 721–730
-
-
Cha, M.1
Mislove, A.2
Gummadi, K.P.3
-
17
-
-
37949004300
-
Data mining for imbalanced datasets: an overview
-
Maimon O, Rokach L, (eds), Springer, Boston
-
Chawla NV (2005) Data mining for imbalanced datasets: an overview. In: Maimon O, Rokach L (eds) Data mining and knowledge discovery handbook. Springer, Boston, pp 853–867
-
(2005)
Data mining and knowledge discovery handbook
, pp. 853-867
-
-
Chawla, N.V.1
-
19
-
-
9444297357
-
Smoteboost: improving prediction of the minority class in boosting
-
Lavrač N, Gamberger D, Todorovski L, Blockeel H, (eds), Springer, Berlin
-
Chawla NV, Lazarevic A, Hall LO, Bowyer KW (2003) Smoteboost: improving prediction of the minority class in boosting. In: Lavrač N, Gamberger D, Todorovski L, Blockeel H (eds) Knowledge discovery in databases: PKDD. Springer, Berlin, pp 107–119
-
(2003)
Knowledge discovery in databases: PKDD
, pp. 107-119
-
-
Chawla, N.V.1
Lazarevic, A.2
Hall, L.O.3
Bowyer, K.W.4
-
20
-
-
27144549260
-
Editorial: special issue on learning from imbalanced data sets
-
Chawla NV, Japkowicz N, Kotcz A (2004) Editorial: special issue on learning from imbalanced data sets. SIGKDD Explor Newsl 6(1):1–6. doi:10.1145/1007730.1007733
-
(2004)
SIGKDD Explor Newsl
, vol.6
, Issue.1
, pp. 1-6
-
-
Chawla, N.V.1
Japkowicz, N.2
Kotcz, A.3
-
21
-
-
84898796363
-
Big data: a survey
-
Chen M, Mao S, Liu Y (2014) Big data: a survey. Mob Netw Appl 19(2):171–209. doi:10.1007/s11036-013-0489-0
-
(2014)
Mob Netw Appl
, vol.19
, Issue.2
, pp. 171-209
-
-
Chen, M.1
Mao, S.2
Liu, Y.3
-
23
-
-
29644438050
-
Statistical comparisons of classifiers over multiple data sets
-
Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7(Jan):1–30
-
(2006)
J Mach Learn Res
, vol.7
, Issue.Jan
, pp. 1-30
-
-
Demšar, J.1
-
26
-
-
50949133669
-
LIBLINEAR: a library for large linear classification
-
Fan RE, Chang KW, Hsieh CJ, Wang XR, Lin CJ (2008) LIBLINEAR: a library for large linear classification. J Mach Learn Res 9:1871–1874
-
(2008)
J Mach Learn Res
, vol.9
, pp. 1871-1874
-
-
Fan, R.E.1
Chang, K.W.2
Hsieh, C.J.3
Wang, X.R.4
Lin, C.J.5
-
27
-
-
85040377067
-
-
Fan W, Stolfo SJ, Zhang J, Chan PK (1999) AdaCost: Misclassification cost-sensitive boosting. In: Proceedings of the sixteenth international conference on machine learning, Morgan Kaufmann Publishers Inc., San Francisco, ICML ’99, pp 97–105
-
(1999)
AdaCost: Misclassification cost-sensitive boosting. In: Proceedings of the sixteenth international conference on machine learning, Morgan Kaufmann Publishers Inc., San Francisco, ICML ’99, pp 97–105
-
-
Fan, W.1
Stolfo, S.J.2
Zhang, J.3
Chan, P.K.4
-
28
-
-
33646023117
-
An introduction to ROC analysis
-
Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27(8):861–874. doi:10.1016/j.patrec.2005.10.010
-
(2006)
Pattern Recognit Lett
, vol.27
, Issue.8
, pp. 861-874
-
-
Fawcett, T.1
-
29
-
-
20444364008
-
Comparison of distance measures in cluster analysis with dichotomous data
-
Finch H (2005) Comparison of distance measures in cluster analysis with dichotomous data. J Data Sci 3(1):85–100
-
(2005)
J Data Sci
, vol.3
, Issue.1
, pp. 85-100
-
-
Finch, H.1
-
30
-
-
74049087026
-
Community detection in graphs
-
Fortunato S (2010) Community detection in graphs. Phys Rep 486(35):75–174. doi:10.1016/j.physrep.2009.11.002
-
(2010)
Phys Rep
, vol.486
, Issue.35
, pp. 75-174
-
-
Fortunato, S.1
-
31
-
-
84875251066
-
A neural network algorithm for semi-supervised node label learning from unbalanced data
-
Frasca M, Bertoni A, Re M, Valentini G (2013) A neural network algorithm for semi-supervised node label learning from unbalanced data. Neural Netw 43:84–98. doi:10.1016/j.neunet.2013.01.021
-
(2013)
Neural Netw
, vol.43
, pp. 84-98
-
-
Frasca, M.1
Bertoni, A.2
Re, M.3
Valentini, G.4
-
32
-
-
84944811700
-
The use of ranks to avoid the assumption of normality implicit in the analysis of variance
-
Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J Am Stat Assoc 32(200):675–701
-
(1937)
J Am Stat Assoc
, vol.32
, Issue.200
, pp. 675-701
-
-
Friedman, M.1
-
33
-
-
84940247545
-
Boosting support vector machines
-
In:, Post Proceedings, IBaI Publishing
-
García E, Lozano F (2007) Boosting support vector machines. In: Machine learning and data mining in pattern recognition, 5th international conference, MLDM 2007, Leipzig, Germany, July 18–20, Post Proceedings, IBaI Publishing, pp 153–167
-
(2007)
Machine learning and data mining in pattern recognition, 5th international conference, MLDM 2007, Leipzig, Germany, July
, vol.18-20
, pp. 153-167
-
-
García, E.1
Lozano, F.2
-
34
-
-
84966280501
-
A comparative evaluation of unsupervised anomaly detection algorithms for multivariate data
-
Goldstein M, Uchida S (2016) A comparative evaluation of unsupervised anomaly detection algorithms for multivariate data. PLoS ONE 11(4):1–31. doi:10.1371/journal.pone.0152173
-
(2016)
PLoS ONE
, vol.11
, Issue.4
, pp. 1-31
-
-
Goldstein, M.1
Uchida, S.2
-
35
-
-
84872050981
-
Characterization and detection of taxpayers with false invoices using data mining techniques
-
Gonzlez PC, Velsquez JD (2013) Characterization and detection of taxpayers with false invoices using data mining techniques. Exp Syst Appl 40(5):1427–1436. doi:10.1016/j.eswa.2012.08.051
-
(2013)
Exp Syst Appl
, vol.40
, Issue.5
, pp. 1427-1436
-
-
Gonzlez, P.C.1
Velsquez, J.D.2
-
36
-
-
34548821644
-
Module identification in bipartite and directed networks
-
Guimerà R, Sales-Pardo M, Amaral LAN (2007) Module identification in bipartite and directed networks. Phys Rev E 76(036):102. doi:10.1103/PhysRevE.76.036102
-
(2007)
Phys Rev E
, vol.76
, Issue.36
, pp. 102
-
-
Guimerà, R.1
Sales-Pardo, M.2
Amaral, L.A.N.3
-
37
-
-
27144479454
-
Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach
-
Guo H, Viktor HL (2004) Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach. SIGKDD Explor Newsl 6(1):30–39. doi:10.1145/1007730.1007736
-
(2004)
SIGKDD Explor Newsl
, vol.6
, Issue.1
, pp. 30-39
-
-
Guo, H.1
Viktor, H.L.2
-
38
-
-
57649123451
-
On the class imbalance problem. In: 2008 fourth international conference on natural computation
-
Y, G, vol
-
Guo X, Yin Y, Dong C, Yang G, Zhou G (2008) On the class imbalance problem. In: 2008 fourth international conference on natural computation, IEEE, vol 4, pp 192–201. doi:10.1109/ICNC.2008.871
-
(2008)
IEEE
, vol.4
, pp. 192-201
-
-
Yin, G.X.1
Yang, D.C.2
Zhou, G.3
-
39
-
-
27144501672
-
Borderline-SMOTE: a new over-sampling method in imbalanced data sets learning
-
Huang D, Zhang X-P, Huang G-B, (eds), Springer, Berlin
-
Han H, Wang WY, Mao BH (2005) Borderline-SMOTE: a new over-sampling method in imbalanced data sets learning. In: Huang D, Zhang X-P, Huang G-B (eds) Advances in intelligent computing. Springer, Berlin, pp 878–887
-
(2005)
Advances in intelligent computing
, pp. 878-887
-
-
Han, H.1
Wang, W.Y.2
Mao, B.H.3
-
40
-
-
68549133155
-
Learning from imbalanced data
-
He H, Garcia EA (2009) Learning from imbalanced data. IEEE Trans Knowl Data Eng 21(9):1263–1284. doi:10.1109/TKDE.2008.239
-
(2009)
IEEE Trans Knowl Data Eng
, vol.21
, Issue.9
, pp. 1263-1284
-
-
He, H.1
Garcia, E.A.2
-
41
-
-
56349089205
-
-
He H, Bai Y, Garcia EA, Li S (2008) ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In: 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence), IEEE, pp 1322–1328. doi:10.1109/IJCNN.2008.4633969
-
(2008)
ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In: 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence), IEEE, pp 1322–1328
-
-
He, H.1
Bai, Y.2
Garcia, E.A.3
Li, S.4
-
42
-
-
0002294347
-
A simple sequentially rejective multiple test procedure
-
Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6(2):65–70
-
(1979)
Scand J Stat
, vol.6
, Issue.2
, pp. 65-70
-
-
Holm, S.1
-
43
-
-
0036505670
-
A comparison of methods for multiclass support vector machines
-
Hsu CW, Lin CJ (2002) A comparison of methods for multiclass support vector machines. IEEE Trans Neural Netw 13(2):415–425. doi:10.1109/72.991427
-
(2002)
IEEE Trans Neural Netw
, vol.13
, Issue.2
, pp. 415-425
-
-
Hsu, C.W.1
Lin, C.J.2
-
45
-
-
0001750957
-
Approximations of the critical region of the Friedman statistic
-
Iman RL, Davenport JM (1980) Approximations of the critical region of the Friedman statistic. Commun Stat Theory Methods 9(6):571–595
-
(1980)
Commun Stat Theory Methods
, vol.9
, Issue.6
, pp. 571-595
-
-
Iman, R.L.1
Davenport, J.M.2
-
46
-
-
27144540575
-
Class imbalances versus small disjuncts
-
Jo T, Japkowicz N (2004) Class imbalances versus small disjuncts. ACM SIGKDD Explor Newsl 6(1):40–49. doi:10.1145/1007730.1007737
-
(2004)
ACM SIGKDD Explor Newsl
, vol.6
, Issue.1
, pp. 40-49
-
-
Jo, T.1
Japkowicz, N.2
-
47
-
-
84991624961
-
Predictive modeling with big data: is bigger really better?
-
Junqué de Fortuny E, Martens D, Provost F (2014a) Predictive modeling with big data: is bigger really better? Big Data 1(4):215–226. doi:10.1089/big.2013.0037
-
(2014)
Big Data
, vol.1
, Issue.4
, pp. 215-226
-
-
Junqué de Fortuny, E.1
Martens, D.2
Provost, F.3
-
48
-
-
84907026917
-
Corporate residence fraud detection
-
Stankova M, Moeyersoms J, Minnaert B, Provost F, Martens D (2014b) Corporate residence fraud detection. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, New York, KDD ’14, pp 1650–1659. doi:10.1145/2623330.2623333
-
(2014)
In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, New York, KDD ’14, pp 1650–1659
-
-
Stankova, M.1
Moeyersoms, J.2
Minnaert, B.3
Provost, F.4
Martens, D.5
-
50
-
-
0001972236
-
Addressing the curse of imbalanced training sets: one-sided selection
-
In: Morgan Kaufmann Publishers Inc., San Francisco, CA, USA
-
Kubat M, Matwin S (1997) Addressing the curse of imbalanced training sets: one-sided selection. In: Proceedings of the fourteenth international conference on machine learning. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp 179–186
-
(1997)
Proceedings of the fourteenth international conference on machine learning
, pp. 179-186
-
-
Kubat, M.1
Matwin, S.2
-
51
-
-
71849108522
-
Community detection algorithms: a comparative analysis
-
Lancichinetti A, Fortunato S (2009) Community detection algorithms: a comparative analysis. Phys Rev E 80(056):117. doi:10.1103/PhysRevE.80.056117
-
(2009)
Phys Rev E
, vol.80
, Issue.56
, pp. 117
-
-
Lancichinetti, A.1
Fortunato, S.2
-
53
-
-
77955067099
-
Weighted area under the receiver operating characteristic curve and its application to gene selection
-
Li J, Fine JP (2010) Weighted area under the receiver operating characteristic curve and its application to gene selection. J R Stat Soc Series C (Appl Stat) 59(4):673–692. doi:10.1111/j.1467-9876.2010.00713.x
-
(2010)
J R Stat Soc Series C (Appl Stat)
, vol.59
, Issue.4
, pp. 673-692
-
-
Li, J.1
Fine, J.P.2
-
54
-
-
44649197212
-
AdaBoost with SVM-based component classifiers
-
Li X, Wang L, Sung E (2008) AdaBoost with SVM-based component classifiers. Eng Appl Artif Intell 21(5):785–795. doi:10.1016/j.engappai.2007.07.001
-
(2008)
Eng Appl Artif Intell
, vol.21
, Issue.5
, pp. 785-795
-
-
Li, X.1
Wang, L.2
Sung, E.3
-
57
-
-
64049108468
-
Exploratory undersampling for class-imbalance learning
-
Liu XY, Wu J, Zhou ZH (2009) Exploratory undersampling for class-imbalance learning. IEEE Trans Syst Man Cybern B (Cybern) 39(2):539–550. doi:10.1109/TSMCB.2008.2007853
-
(2009)
IEEE Trans Syst Man Cybern B (Cybern)
, vol.39
, Issue.2
, pp. 539-550
-
-
Liu, X.Y.1
Wu, J.2
Zhou, Z.H.3
-
58
-
-
77952238401
-
A tutorial on support vector machine-based methods for classification problems in chemometrics
-
Luts J, Ojeda F, Van de Plas R, De Moor B, Van Huffel S, Suykens JA (2010) A tutorial on support vector machine-based methods for classification problems in chemometrics. Anal Chim Acta 665(2):129–145. doi:10.1016/j.aca.2010.03.030
-
(2010)
Anal Chim Acta
, vol.665
, Issue.2
, pp. 129-145
-
-
Luts, J.1
Ojeda, F.2
Van de Plas, R.3
De Moor, B.4
Van Huffel, S.5
Suykens, J.A.6
-
59
-
-
34249102504
-
Classification in networked data: a toolkit and a univariate case study
-
Macskassy SA, Provost F (2007) Classification in networked data: a toolkit and a univariate case study. J Mach Learn Res 8(May):935–983
-
(2007)
J Mach Learn Res
, vol.8
, Issue.May
, pp. 935-983
-
-
Macskassy, S.A.1
Provost, F.2
-
60
-
-
84919337364
-
Explaining data-driven document classifications
-
Martens D, Provost F (2014) Explaining data-driven document classifications. MIS Q 38(1):73–100
-
(2014)
MIS Q
, vol.38
, Issue.1
, pp. 73-100
-
-
Martens, D.1
Provost, F.2
-
61
-
-
85013446601
-
Mining massive fine-grained behavior data to improve predictive analytics
-
Martens D, Provost F, Clark J, Junqué de Fortuny E (2016) Mining massive fine-grained behavior data to improve predictive analytics. MIS Q 40(4):869–888
-
(2016)
MIS Q
, vol.40
, Issue.4
, pp. 869-888
-
-
Martens, D.1
Provost, F.2
Clark, J.3
Junqué de Fortuny, E.4
-
62
-
-
40649126091
-
Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance
-
Mazurowski MA, Habas PA, Zurada JM, Lo JY, Baker JA, Tourassi GD (2008) Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance. Neural Netw 21(23):427–436. doi:10.1016/j.neunet.2007.12.031
-
(2008)
Neural Netw
, vol.21
, Issue.23
, pp. 427-436
-
-
Mazurowski, M.A.1
Habas, P.A.2
Zurada, J.M.3
Lo, J.Y.4
Baker, J.A.5
Tourassi, G.D.6
-
63
-
-
33947284406
-
Boosted classification trees and class probability/quantile estimation
-
Mease D, Wyner AJ, Buja A (2007) Boosted classification trees and class probability/quantile estimation. J Mach Learn Res 8:409–439
-
(2007)
J Mach Learn Res
, vol.8
, pp. 409-439
-
-
Mease, D.1
Wyner, A.J.2
Buja, A.3
-
65
-
-
37649028224
-
Finding and evaluating community structure in networks
-
Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(026):113. doi:10.1103/PhysRevE.69.026113
-
(2004)
Phys Rev E
, vol.69
, Issue.26
, pp. 113
-
-
Newman, M.E.J.1
Girvan, M.2
-
66
-
-
14344249889
-
-
Ng AY (2004) Feature selection, L1 vs. L2 regularization, and rotational invariance. In: Proceedings of the twenty-first international conference on machine learning, ACM, New York, NY, USA, ICML ’04, p 78. doi:10.1145/1015330.1015435
-
(2004)
Feature selection, L1 vs. L2 regularization, and rotational invariance. In: Proceedings of the twenty-first international conference on machine learning, ACM, New York, NY, USA, ICML ’04, p 78
-
-
Ng, A.Y.1
-
68
-
-
78651084785
-
The application of data mining techniques in financial fraud detection: a classification framework and an academic review of literature
-
Ngai E, Hu Y, Wong Y, Chen Y, Sun X (2011) The application of data mining techniques in financial fraud detection: a classification framework and an academic review of literature. Decis Support Syst 50(3):559–569. doi:10.1016/j.dss.2010.08.006
-
(2011)
Decis Support Syst
, vol.50
, Issue.3
, pp. 559-569
-
-
Ngai, E.1
Hu, Y.2
Wong, Y.3
Chen, Y.4
Sun, X.5
-
69
-
-
0003243224
-
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In: Smola AJ, Bartlett P, Schoelkopf B, Schuurmans D (eds) Advances in large-margin classifiers
-
Platt JC (1999) Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In: Smola AJ, Bartlett P, Schoelkopf B, Schuurmans D (eds) Advances in large-margin classifiers. MIT Press, pp 61–74
-
(1999)
MIT Press
, pp. 61-74
-
-
Platt, J.C.1
-
72
-
-
70350645569
-
-
Provost F, Dalessandro B, Hook R, Zhang X, Murray A (2009) Audience selection for on-line brand advertising: privacy-friendly social network targeting. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, New York, NY, USA, KDD ’09, pp 707–716. doi:10.1145/1557019.1557098
-
(2009)
Audience selection for on-line brand advertising: privacy-friendly social network targeting. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, New York, NY, USA, KDD ’09, pp 707–716
-
-
Provost, F.1
Dalessandro, B.2
Hook, R.3
Zhang, X.4
Murray, A.5
-
73
-
-
32344438970
-
Extreme re-balancing for SVMs: a case study
-
Raskutti B, Kowalczyk A (2004) Extreme re-balancing for SVMs: a case study. SIGKDD Explor Newsl 6(1):60–69. doi:10.1145/1007730.1007739
-
(2004)
SIGKDD Explor Newsl
, vol.6
, Issue.1
, pp. 60-69
-
-
Raskutti, B.1
Kowalczyk, A.2
-
74
-
-
39549086558
-
Maps of random walks on complex networks reveal community structure
-
Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci 105(4):1118–1123. doi:10.1073/pnas.0706851105
-
(2008)
Proc Natl Acad Sci
, vol.105
, Issue.4
, pp. 1118-1123
-
-
Rosvall, M.1
Bergstrom, C.T.2
-
75
-
-
84880692052
-
-
Schapire RE (1999) A brief introduction to boosting. In: Proceedings of the 16th international joint conference on artificial intelligence—volume 2. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, IJCAI’99, pp 1401–1406
-
(1999)
A brief introduction to boosting. In: Proceedings of the 16th international joint conference on artificial intelligence—volume 2. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, IJCAI’99, pp 1401–1406
-
-
Schapire, R.E.1
-
76
-
-
0033281701
-
Improved boosting algorithms using confidence-rated predictions
-
Schapire RE, Singer Y (1999) Improved boosting algorithms using confidence-rated predictions. Mach Learn 37(3):297–336. doi:10.1023/A:1007614523901
-
(1999)
Mach Learn
, vol.37
, Issue.3
, pp. 297-336
-
-
Schapire, R.E.1
Singer, Y.2
-
77
-
-
85006137683
-
Analyzing behavioral big data: methodological, practical, ethical, and moral issues
-
Shmueli G (2017) Analyzing behavioral big data: methodological, practical, ethical, and moral issues. Qual Eng 29(1):57–74. doi:10.1080/08982112.2016.1210979
-
(2017)
Qual Eng
, vol.29
, Issue.1
, pp. 57-74
-
-
Shmueli, G.1
-
78
-
-
84931080969
-
Learning from imbalanced data using ensemble methods and cluster-based undersampling
-
H, In
-
Sobhani P, Viktor H, Matwin S (2015) Learning from imbalanced data using ensemble methods and cluster-based undersampling. In: New frontiers in mining complex patterns: third international workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers, Springer International Publishing, Cham, pp 69–83. doi:10.1007/978-3-319-17876-9_5
-
(2015)
New frontiers in mining complex patterns: third international workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers, Springer International Publishing, Cham
, pp. 69-83
-
-
Viktor, S.P.1
Matwin, S.2
-
81
-
-
34547673383
-
Cost-sensitive boosting for classification of imbalanced data
-
Sun Y, Kamel MS, Wong AK, Wang Y (2007) Cost-sensitive boosting for classification of imbalanced data. Pattern Recognit 40(12):3358–3378. doi:10.1016/j.patcog.2007.04.009
-
(2007)
Pattern Recognit
, vol.40
, Issue.12
, pp. 3358-3378
-
-
Sun, Y.1
Kamel, M.S.2
Wong, A.K.3
Wang, Y.4
-
82
-
-
0037695279
-
-
World Scientific, Singapore
-
Suykens JA, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J, Suykens J, Van Gestel T (2002) Least squares support vector machines. World Scientific, Singapore
-
(2002)
Least squares support vector machines
-
-
Suykens, J.A.1
Van Gestel, T.2
De Brabanter, J.3
De Moor, B.4
Vandewalle, J.5
Suykens, J.6
Van Gestel, T.7
-
83
-
-
84937796378
-
Enn: Extended nearest neighbor method for pattern recognition [research frontier]
-
Tang B, He H (2015) Enn: Extended nearest neighbor method for pattern recognition [research frontier]. IEEE Comput Intell Mag 10(3):52–60. doi:10.1109/MCI.2015.2437512
-
(2015)
IEEE Comput Intell Mag
, vol.10
, Issue.3
, pp. 52-60
-
-
Tang, B.1
He, H.2
-
84
-
-
61549114384
-
SVMs modeling for highly imbalanced classification
-
Tang Y, Zhang YQ, Chawla NV, Krasser S (2009) SVMs modeling for highly imbalanced classification. IEEE Trans Syst Man Cybern B (Cybern) 39(1):281–288. doi:10.1109/TSMCB.2008.2002909
-
(2009)
IEEE Trans Syst Man Cybern B (Cybern)
, vol.39
, Issue.1
, pp. 281-288
-
-
Tang, Y.1
Zhang, Y.Q.2
Chawla, N.V.3
Krasser, S.4
-
85
-
-
85040330871
-
-
Tobback E, Moeyersoms J, Stankova M, Martens D (2016) Bankruptcy prediction for SMEs using relational data. Working paper 2016004, University of Antwerp, Faculty of Applied Economics
-
(2016)
Bankruptcy prediction for SMEs using relational data. Working paper 2016004, University of Antwerp, Faculty of Applied Economics
-
-
Tobback, E.1
Moeyersoms, J.2
Stankova, M.3
Martens, D.4
-
86
-
-
83955164226
-
New insights into churn prediction in the telecommunication sector: a profit driven data mining approach
-
Verbeke W, Dejaeger K, Martens D, Hur J, Baesens B (2012) New insights into churn prediction in the telecommunication sector: a profit driven data mining approach. Eur J Oper Res 218(1):211–229. doi:10.1016/j.ejor.2011.09.031
-
(2012)
Eur J Oper Res
, vol.218
, Issue.1
, pp. 211-229
-
-
Verbeke, W.1
Dejaeger, K.2
Martens, D.3
Hur, J.4
Baesens, B.5
-
87
-
-
85040318316
-
-
Veropoulos K, Campbell I, Cristianini N (1999) Controlling the sensitivity of support vector machines. In: Proceedings of the international joint conference on artificial intelligence, Stockholm, Sweden (IJCAI99), pp 55–60
-
(1999)
Controlling the sensitivity of support vector machines. In: Proceedings of the international joint conference on artificial intelligence, Stockholm, Sweden (IJCAI99), pp 55–60
-
-
Veropoulos, K.1
Campbell, I.2
Cristianini, N.3
-
88
-
-
57849084755
-
Transaction aggregation as a strategy for credit card fraud detection
-
Whitrow C, Hand DJ, Juszczak P, Weston D, Adams NM (2009) Transaction aggregation as a strategy for credit card fraud detection. Data Min Knowl Discov 18(1):30–55. doi:10.1007/s10618-008-0116-z
-
(2009)
Data Min Knowl Discov
, vol.18
, Issue.1
, pp. 30-55
-
-
Whitrow, C.1
Hand, D.J.2
Juszczak, P.3
Weston, D.4
Adams, N.M.5
-
89
-
-
84956981949
-
-
Wickramaratna J, Holden SB, Buxton BF (2001) Performance degradation in boosting. In: Proceedings of the second international workshop on multiple classifier systems, Springer, London, UK, MCS ’01, pp 11–21
-
(2001)
Performance degradation in boosting. In: Proceedings of the second international workshop on multiple classifier systems, Springer, London, UK, MCS ’01, pp 11–21
-
-
Wickramaratna, J.1
Holden, S.B.2
Buxton, B.F.3
-
90
-
-
58349090428
-
Cluster-based under-sampling approaches for imbalanced data distributions
-
Yen SJ, Lee YS (2009) Cluster-based under-sampling approaches for imbalanced data distributions. Exp Syst Appl 36(3, Part 1):5718–5727. doi:10.1016/j.eswa.2008.06.108
-
(2009)
Exp Syst Appl
, vol.36
, Issue.3
, pp. 5718-5727
-
-
Yen, S.J.1
Lee, Y.S.2
-
91
-
-
85040369951
-
-
Yu HF, Lo HY, Hsieh HP, Lou JK, McKenzie TG, Chou JW, Chung PH, Ho CH, Chang CF, Wei YH, et al (2010) Feature engineering and classifier ensemble for kdd cup 2010. In: Proceedings of the KDD Cup 2010 Workshop, pp 1–16
-
(2010)
Feature engineering and classifier ensemble for kdd cup 2010. In: Proceedings of the KDD Cup 2010 Workshop, pp 1–16
-
-
Yu, H.F.1
Lo, H.Y.2
Hsieh, H.P.3
Lou, J.K.4
McKenzie, T.G.5
Chou, J.W.6
Chung, P.H.7
Ho, C.H.8
Chang, C.F.9
Wei, Y.H.10
-
92
-
-
0035751898
-
-
Zha H, He X, Ding C, Simon H, Gu M (2001) Bipartite graph partitioning and data clustering. In: Proceedings of the tenth international conference on information and knowledge management, ACM, New York, NY, USA, CIKM ’01, pp 25–32. doi:10.1145/502585.502591
-
(2001)
Bipartite graph partitioning and data clustering. In: Proceedings of the tenth international conference on information and knowledge management, ACM, New York, NY, USA, CIKM ’01, pp 25–32
-
-
Zha, H.1
He, X.2
Ding, C.3
Simon, H.4
Gu, M.5
-
94
-
-
42149129805
-
-
Ziegler CN, McNee SM, Konstan JA, Lausen G (2005) Improving recommendation lists through topic diversification. In: Proceedings of the 14th international conference on world wide web, ACM, New York, NY, USA, WWW ’05, pp 22–32. doi:10.1145/1060745.1060754
-
(2005)
Improving recommendation lists through topic diversification. In: Proceedings of the 14th international conference on world wide web, ACM, New York, NY, USA, WWW ’05, pp 22–32
-
-
Ziegler, C.N.1
McNee, S.M.2
Konstan, J.A.3
Lausen, G.4
|