-
1
-
-
0032786569
-
Improving support vector machine classifiers by modifying kernel functions
-
S. Amari and S. Wu, "Improving Support Vector Machine Classifiers by Modifying Kernel Functions," Neural Networks, vol. 12, no. 6, pp. 783-789, 1999.
-
(1999)
Neural Networks
, vol.12
, Issue.6
, pp. 783-789
-
-
Amari, S.1
Wu, S.2
-
2
-
-
0031191630
-
The use of the area under the roc curve in the evaluation of machine learning algorithms
-
A.P. Bradley, "The Use of the Area under the Roc Curve in the Evaluation of Machine Learning Algorithms," Pattern Recognition, vol. 30, no. 7, pp. 1145-1159, 1997.
-
(1997)
Pattern Recognition
, vol.30
, Issue.7
, pp. 1145-1159
-
-
Bradley, A.P.1
-
3
-
-
0030211964
-
Bagging predictors
-
L. Breiman, "Bagging Predictors," Machine Learning, vol. 24, no. 2, pp. 123-140, 1996.
-
(1996)
Machine Learning
, vol.24
, Issue.2
, pp. 123-140
-
-
Breiman, L.1
-
5
-
-
0002500236
-
Improving minority class prediction using case-specific feature weights
-
C. Cardie and N. Howe, "Improving Minority Class Prediction Using Case-Specific Feature Weights," Proc. 14th Int'l Conf. Machine Learning, pp. 57-65, 1997.
-
(1997)
Proc. 14th Int'l Conf. Machine Learning
, pp. 57-65
-
-
Cardie, C.1
Howe, N.2
-
6
-
-
1942482069
-
Learning with non-uniform class and cost distributions: Effects and a distributed multi-classifier approach
-
P. Chan and S. Stolfo, "Learning with Non-Uniform Class and Cost Distributions: Effects and a Distributed Multi-Classifier Approach," Proc. Workshop Notes KDD-98 Distributed Data Mining, pp. 1-9, 1998.
-
(1998)
Proc. Workshop Notes KDD-98 Distributed Data Mining
, pp. 1-9
-
-
Chan, P.1
Stolfo, S.2
-
7
-
-
0346586663
-
Smote: Synthetic minority over-sampling technique
-
N. Chawla, K. Bowyer, L. Hall, and W.P. Kegelmeyer, "Smote: Synthetic Minority Over-Sampling Technique," J. Artificial Intelligence and Research, vol. 16, pp. 321-357, 2002.
-
(2002)
J. Artificial Intelligence and Research
, vol.16
, pp. 321-357
-
-
Chawla, N.1
Bowyer, K.2
Hall, L.3
Kegelmeyer, W.P.4
-
8
-
-
0041995195
-
On kernel target alignment
-
N. Cristianini, J. Shawe-Taylor, and J. Kandola, "On Kernel Target Alignment," Proc. Neural Information Processing Systems, pp. 367-373, 2001.
-
(2001)
Proc. Neural Information Processing Systems
, pp. 367-373
-
-
Cristianini, N.1
Shawe-Taylor, J.2
Kandola, J.3
-
9
-
-
0000406788
-
Solving multiclass learning problems via error-correcting output codes
-
T. Dietterich and G. Bakiri, "Solving Multiclass Learning Problems via Error-Correcting Output Codes," J. Artifical Intelligence Research, vol. 2, pp. 263-286, 1995.
-
(1995)
J. Artifical Intelligence Research
, vol.2
, pp. 263-286
-
-
Dietterich, T.1
Bakiri, G.2
-
10
-
-
0004708854
-
Exploiting the cost (in)sensitivity of decision tree splitting criteria
-
C. Drummond and R. Holte, "Exploiting the Cost (in)Sensitivity of Decision Tree Splitting Criteria," Proc. 17th Int'l Conf. Machine Learning, pp. 239-246, 2000.
-
(2000)
Proc. 17th Int'l Conf. Machine Learning
, pp. 239-246
-
-
Drummond, C.1
Holte, R.2
-
11
-
-
0013113240
-
Adaptive fraud detection
-
T. Fawcett and F. Provost, "Adaptive Fraud Detection," Data Mining and Knowledge Discovery, vol. 1, no. 3, pp. 291-316, 1997.
-
(1997)
Data Mining and Knowledge Discovery
, vol.1
, Issue.3
, pp. 291-316
-
-
Fawcett, T.1
Provost, F.2
-
13
-
-
0003684449
-
-
New York: Springer
-
T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer, 2001.
-
(2001)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
14
-
-
84957069814
-
Text categorization with support vector machines: Learning with many relevant features
-
T. Joachims, "Text Categorization with Support Vector Machines: Learning with Many Relevant Features," Proc. 10th European Conf. Machine Learning, pp. 137-142, 1998.
-
(1998)
Proc. 10th European Conf. Machine Learning
, pp. 137-142
-
-
Joachims, T.1
-
17
-
-
0001972236
-
Addressing the curse of imbalanced training sets: One-sided selection
-
M. Kubat and S. Matwin, "Addressing the Curse of Imbalanced Training Sets: One-Sided Selection," Proc. 14th Int'l Conf. Machine Learning, pp. 179-186, 1997.
-
(1997)
Proc. 14th Int'l Conf. Machine Learning
, pp. 179-186
-
-
Kubat, M.1
Matwin, S.2
-
19
-
-
0036161029
-
Support vector machines for classification in nonstandard situations
-
Y. Lin, Y. Lee, and G. Wahba, "Support Vector Machines for Classification in Nonstandard Situations," Machine Learning, vol. 46, pp. 191-202, 2002.
-
(2002)
Machine Learning
, vol.46
, pp. 191-202
-
-
Lin, Y.1
Lee, Y.2
Wahba, G.3
-
20
-
-
0036630282
-
A solution for imbalanced training sets problem by combnet-ii and its application on fug forecasting
-
July
-
A. Nugroho, S. Kuroyanagi, and A. Iwata, "A Solution for Imbalanced Training Sets Problem by Combnet-ii and Its Application on Fug Forecasting," IEICE Trans. Information and Systems, vol. E85-D, no. 7, pp. 1165-1174, July 2002.
-
(2002)
IEICE Trans. Information and Systems
, vol.E85-D
, Issue.7
, pp. 1165-1174
-
-
Nugroho, A.1
Kuroyanagi, S.2
Iwata, A.3
-
21
-
-
0003408420
-
-
Cambridge, Mass.: MIT Press
-
B. Scholkopf and A. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, Mass.: MIT Press, 2002.
-
(2002)
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and beyond
-
-
Scholkopf, B.1
Smola, A.2
-
22
-
-
0034792634
-
Support vector machine active learning for image retrieval
-
S. Tong and E. Chang, "Support Vector Machine Active Learning for Image Retrieval," Proc. ACM Int'l Conf. Multimedia, pp. 107-118, 2001.
-
(2001)
Proc. ACM Int'l Conf. Multimedia
, pp. 107-118
-
-
Tong, S.1
Chang, E.2
-
24
-
-
0002648330
-
Controlling the sensitivity of support vector machines
-
K. Veropoulos, C. Campbell, and N. Cristianini, "Controlling the Sensitivity of Support Vector Machines," Proc. Int'l joint Conf. Artificial Intelligence, pp. 55-60, 1999.
-
(1999)
Proc. Int'l Joint Conf. Artificial Intelligence
, pp. 55-60
-
-
Veropoulos, K.1
Campbell, C.2
Cristianini, N.3
-
25
-
-
20844458491
-
Mining with rarity: A unifying framework
-
June
-
G.M. Weiss, "Mining with Rarity: A Unifying Framework," SIGKDD Explorations, vol. 6, no. 1, pp. 7-19, June 2004.
-
(2004)
SIGKDD Explorations
, vol.6
, Issue.1
, pp. 7-19
-
-
Weiss, G.M.1
-
26
-
-
1442275185
-
Learning when training data are costly: The effect of class distribution on tree induction
-
G.M. Weiss and F. Provost, "Learning When Training Data Are Costly: The Effect of Class Distribution on Tree Induction," J. Artificial Intelligence Research, vol. 19, pp. 315-354, 2003.
-
(2003)
J. Artificial Intelligence Research
, vol.19
, pp. 315-354
-
-
Weiss, G.M.1
Provost, F.2
-
27
-
-
1942451958
-
Adaptive feature-space conformal transformation for imbalanced data learning
-
G. Wu and E. Chang, "Adaptive Feature-Space Conformal Transformation for Imbalanced Data Learning," Proc. 20th Int'l Conf. Machine Learning, pp. 816-823, 2003.
-
(2003)
Proc. 20th Int'l Conf. Machine Learning
, pp. 816-823
-
-
Wu, G.1
Chang, E.2
-
28
-
-
2342569579
-
Multi-camera spatio-temporal fusion and biased sequence-data learning for security surveillance
-
Nov.
-
G. Wu, Y. Wu, L. Jiao, Y.-F. Wang, and E. Chang, "Multi-Camera Spatio-Temporal Fusion and Biased Sequence-Data Learning for Security Surveillance," Proc. ACM Int'l Conf. Multimedia, Nov. 2003.
-
(2003)
Proc. ACM Int'l Conf. Multimedia
-
-
Wu, G.1
Wu, Y.2
Jiao, L.3
Wang, Y.-F.4
Chang, E.5
-
29
-
-
1942516495
-
New v-suppurt vector machines and their sequential minimal optimization
-
X. Wu and R. Srihari, "New v-Suppurt Vector Machines and Their Sequential Minimal Optimization," Proc. 20th Int'l Conf. Machine Learning, 2003.
-
(2003)
Proc. 20th Int'l Conf. Machine Learning
-
-
Wu, X.1
Srihari, R.2
|