-
1
-
-
22944452794
-
Applying support vector machines to unbalanced datasets
-
R. Akbani, S. Kwek, and N. Japkowicz. Applying support vector machines to unbalanced datasets. In Lecture Notes in Computer Science, volume 3201, pages 39-50, 2004.
-
(2004)
Lecture Notes in Computer Science
, vol.3201
, pp. 39-50
-
-
Akbani, R.1
Kwek, S.2
Japkowicz, N.3
-
2
-
-
27144531570
-
study of the behavior of several methods for balancing machine learning training data
-
A, :20-29
-
Gustavo E. A. P. A. Batista, Ronaldo C. Prati, and Maria Carolina Monard. A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor. Newsl., 6(1):20-29, 2004.
-
(2004)
SIGKDD Explor. Newsl
, vol.6
, Issue.1
-
-
Batista, G.E.A.P.A.1
Prati, R.C.2
Carolina Monard, M.3
-
3
-
-
68549121111
-
C4.5 and unbalanced Data sets: Investigating the effect of sampling method, probabilistic estimate, and decision tree structure
-
Nitesh V. Chawla. C4.5 and unbalanced Data sets: Investigating the effect of sampling method, probabilistic estimate, and decision tree structure. In Workshop on Learning from Imbalanced Datasets (ICML'03), 2003.
-
(2003)
Workshop on Learning from Imbalanced Datasets (ICML'03)
-
-
Chawla, N.V.1
-
4
-
-
0346586663
-
SMOTE: Synthetic Minority Over-sampling TEchnique
-
N.V. Chawla, K.W. Bowyer, L.O. Hall, and W.P. Kegelmeyer. SMOTE: Synthetic Minority Over-sampling TEchnique. In Journal of Artificial Intelligence Research, volume 16, pages 321-357, 2002.
-
(2002)
Journal of Artificial Intelligence Research
, vol.16
, pp. 321-357
-
-
Chawla, N.V.1
Bowyer, K.W.2
Hall, L.O.3
Kegelmeyer, W.P.4
-
5
-
-
33745787554
-
Using random forest to learn unbalanced data
-
Statistics Department, University of California at Berkeley
-
C. Chen, A. Liaw, and L. Breiman. Using random forest to learn unbalanced data. Technical Report Technical report 666, Statistics Department, University of California at Berkeley, 2004.
-
(2004)
Technical Report Technical report
, vol.666
-
-
Chen, C.1
Liaw, A.2
Breiman, L.3
-
6
-
-
42549115494
-
Representing association classification rules mined from health data
-
J. Chen, H. He, J. Li, H. Jin, D. McAullay, G. Williams, R. Sparks, and C. Kelman. Representing association classification rules mined from health data. In International Conference on Knowledge-Based & Intelligent Information & Engineering Systems, 2005.
-
(2005)
International Conference on Knowledge-Based & Intelligent Information & Engineering Systems
-
-
Chen, J.1
He, H.2
Li, J.3
Jin, H.4
McAullay, D.5
Williams, G.6
Sparks, R.7
Kelman, C.8
-
7
-
-
0242372103
-
Data Imbalance in Surveillance of Nosocomial Infections
-
Hugo Sax Gilles Cohen, Melanie Hilario and Stephane Hugonnet. Data Imbalance in Surveillance of Nosocomial Infections. In Lecture Notes in Computer Science, volume 2868, pages 109-117, 2003.
-
(2003)
Lecture Notes in Computer Science
, vol.2868
, pp. 109-117
-
-
Sax, H.1
Cohen, G.2
Hilario, M.3
Hugonnet, S.4
-
8
-
-
27144479454
-
Learning from imbalanced data sets with boosting and data generation: The DataBoost-IM approach
-
30-39
-
Hongyu Guo and Herna L. Viktor. Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach. SIGKDD Explor. Newsl., 6(1):30-39, 2004.
-
(2004)
SIGKDD Explor. Newsl
, vol.6
, Issue.1
-
-
Guo, H.1
Viktor, H.L.2
-
9
-
-
0036083445
-
-
T.K. Ho. A Data Complexity Analysis of Comparative Advantages of Decision Forest Constructors. In Pattern Analysis and Applications, pages 102-112, 2002.
-
T.K. Ho. A Data Complexity Analysis of Comparative Advantages of Decision Forest Constructors. In Pattern Analysis and Applications, pages 102-112, 2002.
-
-
-
-
10
-
-
0000092441
-
The nonlinearity of pattern classifiers
-
A. Hoekstra and R. Duin. The nonlinearity of pattern classifiers. In Proc. of the 13th ICPR, pages 271-275, 1996.
-
(1996)
Proc. of the 13th ICPR
, pp. 271-275
-
-
Hoekstra, A.1
Duin, R.2
-
11
-
-
27144540575
-
Class imbalances versus small disjuncts
-
40-49
-
Taeho Jo and Nathalie Japkowicz. Class imbalances versus small disjuncts. SIGKDD Explor. Newsl., 6(1):40-49, 2004.
-
(2004)
SIGKDD Explor. Newsl
, vol.6
, Issue.1
-
-
Jo, T.1
Japkowicz, N.2
-
15
-
-
0002442796
-
Machine learning in automated text categorization
-
Fabrizio Sebastiani. Machine learning in automated text categorization. ACM Computing Surveys, 34(1): 1-47, 2002.
-
(2002)
ACM Computing Surveys
, vol.34
, Issue.1
, pp. 1-47
-
-
Sebastiani, F.1
-
17
-
-
42549149920
-
-
Sarah Zelikovitz and Haym Hirsh. Improving Short Text Classification Using Unlabeled Background Knowledge. In In Proceedings of the Seventeenth International Conference on Machine Learning, 2000.
-
Sarah Zelikovitz and Haym Hirsh. Improving Short Text Classification Using Unlabeled Background Knowledge. In In Proceedings of the Seventeenth International Conference on Machine Learning, 2000.
-
-
-
-
18
-
-
42549102453
-
-
Jianping Zhang and Inderjeet Mani. kNN Approach to Unbalanced Data Distributions: A Case Study involving Information Extraction. In Workshop on Learning from Imbalanced Datasets (ICML'03), 2003.
-
Jianping Zhang and Inderjeet Mani. kNN Approach to Unbalanced Data Distributions: A Case Study involving Information Extraction. In Workshop on Learning from Imbalanced Datasets (ICML'03), 2003.
-
-
-
|