-
1
-
-
27144549260
-
Editorial: Special issue on learning from imbalanced data sets
-
June
-
N.V. Chawla, N. Japkowicz, and A. Kolcz, "Editorial: Special Issue on Learning from Imbalanced Data Sets," ACM SIGKDD Explorations Newsletter, vol. 6, no. 1, pp. 1-6, June 2004.
-
(2004)
ACM SIGKDD Explorations Newsletter
, vol.6
, Issue.1
, pp. 1-6
-
-
Chawla, N.V.1
Japkowicz, N.2
Kolcz, A.3
-
2
-
-
20844458491
-
Mining with rarity: A unifying framework
-
June
-
G.M. Weiss, "Mining with Rarity: A Unifying Framework," ACM SIGKDD Explorations Newsletter, vol. 6, no. 1, pp. 7-19, June 2004.
-
(2004)
ACM SIGKDD Explorations Newsletter
, vol.6
, Issue.1
, pp. 7-19
-
-
Weiss, G.M.1
-
3
-
-
79551678342
-
Workshop report: Aaai-2000 workshop learning from imbalanced data sets
-
N. Japkowicz and R. Holte, "Workshop Report: AAAI-2000 Workshop Learning from Imbalanced Data Sets," AI Magazine, vol. 22, no. 1, pp. 127-136, 2001
-
(2001)
AI Magazine
, vol.22
, Issue.1
, pp. 127-136
-
-
Japkowicz, N.1
Holte, R.2
-
5
-
-
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," J. Artificial Intelligence Research, vol. 16, pp. 321-357, 2002.
-
(2002)
J. Artificial Intelligence Research
, vol.16
, pp. 321-357
-
-
Chawla, N.V.1
Bowyer, K.W.2
Hall, L.O.3
Kegelmeyer, W.P.4
-
6
-
-
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
-
7
-
-
34547995826
-
Experimental perspectives on learning from imbalanced data
-
J.V. Hulse, T.M. Khoshgoftaar, and A. Napolitano, "Experimental Perspectives on Learning from Imbalanced Data," Proc. 24th Int'l Conf. Machine Learning, pp. 935-942, 2007.
-
(2007)
Proc. 24th Int'l Conf. Machine Learning
, pp. 935-942
-
-
Hulse, J.V.1
Khoshgoftaar, T.M.2
Napolitano, A.3
-
8
-
-
27144531570
-
A study of the behavior of several methods for balancing machine learning training data
-
June
-
G.E.A.P.A. Batista, R.C. Prati, and M.C. Monard, "A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data," ACM SIGKDD Explorations Newsletter, vol. 6, no. 1, pp. 20-29, June 2004.
-
(2004)
ACM SIGKDD Explorations Newsletter
, vol.6
, Issue.1
, pp. 20-29
-
-
Batista, G.E.A.P.A.1
Prati, R.C.2
Monard, M.C.3
-
10
-
-
33750593995
-
EUS svms: Ensemble of under-sampled svms for data imbalance problems
-
Springer, Oct.
-
P. Kang and S. Cho, "EUS SVMs: Ensemble of Under-Sampled SVMs for Data Imbalance Problems," Lecture Notes in Computer Science, pp. 837-846, Springer, Oct. 2006.
-
(2006)
Lecture Notes in Computer Science
, pp. 837-846
-
-
Kang, P.1
Cho, S.2
-
11
-
-
63449090301
-
Learning on the border: Active learning in imbalanced data classification
-
Nov.
-
S. Ertekin, J. Huang, L. Bottou, and C.L. Giles, "Learning on the Border: Active Learning in Imbalanced Data Classification," Proc. ACM Conf. Information and Knowledge Management (CIKM '07), pp. 127-136, Nov. 2007.
-
(2007)
Proc. ACM Conf. Information and Knowledge Management (CIKM '07)
, pp. 127-136
-
-
Ertekin, S.1
Huang, J.2
Bottou, L.3
Giles, C.L.4
-
12
-
-
36448992227
-
Active learning for class imbalance problem
-
July
-
S. Ertekin, J. Huang, and C.L. Giles, "Active Learning for Class Imbalance Problem," Proc. ACM SIGIR '07), pp. 823-824, July 2007.
-
(2007)
Proc. ACM SIGIR '07
, pp. 823-824
-
-
Ertekin, S.1
Huang, J.2
Giles, C.L.3
-
13
-
-
0034807546
-
Knowledge discovery approach to automated cardiac spect diagnosis
-
Oct.
-
L.A. Kurgan, K.J. Cios, R. Tadeusiewicz, M. Ogiela, and L. Goodenday, "Knowledge Discovery Approach to Automated Cardiac SPECT Diagnosis," Artificial Intelligence in Medicine, vol. 23, no. 2, pp. 149-169, Oct. 2001.
-
(2001)
Artificial Intelligence in Medicine
, vol.23
, Issue.2
, pp. 149-169
-
-
Kurgan, L.A.1
Cios, K.J.2
Tadeusiewicz, R.3
Ogiela, M.4
Goodenday, L.5
-
14
-
-
10044280127
-
An in-silico method for prediction of polyadenylation signals in human sequences
-
Dec.
-
H. Liu, H. Han, J. Li, and L. Wong, "An In-Silico Method for Prediction of Polyadenylation Signals in Human Sequences," Proc. 14th Int'l Conf. Genome Informatics, vol. 14, pp. 84-93, Dec. 2003.
-
(2003)
Proc. 14th Int'l Conf. Genome Informatics
, vol.14
, pp. 84-93
-
-
Liu, H.1
Han, H.2
Li, J.3
Wong, L.4
-
15
-
-
33745862379
-
Predicting deleterious nssnps: An analysis of sequence and structural attributes
-
R.J. Dobson, P.B. Munroe, M.J. Caulfield, and M.A.S. Saqi, "Predicting Deleterious nsSNPs: An Analysis of Sequence and Structural Attributes," BMC Bioinformatics, vol. 7, pp. 217-225, 2006.
-
(2006)
BMC Bioinformatics
, vol.7
, pp. 217-225
-
-
Dobson, R.J.1
Munroe, P.B.2
Caulfield, M.J.3
Saqi, M.A.S.4
-
16
-
-
47249093354
-
Asymmetric bagging and feature selection for activities prediction of drug molecules
-
Aug.
-
G.-Z. Li, H.-H. Meng, W.-C. Lu, J.Y. Yang, and M.Q. Yang, "Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules," BMC Bioinformatics, vol. 9, suppl. 6, p. S7, Aug. 2007.
-
(2007)
BMC Bioinformatics
, vol.9
, Issue.SUPPL. 6
-
-
Li, G.-Z.1
Meng, H.-H.2
Lu, W.-C.3
Yang, J.Y.4
Yang, M.Q.5
-
17
-
-
38849163717
-
Glycosylation site prediction using ensembles of support vector machine classifiers
-
Nov.
-
C. Caragea, J. Sinapov, A. Silvescu, D. Dobbs, and V. Honavar, "Glycosylation Site Prediction Using Ensembles of Support Vector Machine Classifiers," BMC Bioinformatics, vol. 8, pp. 438-450, Nov. 2007.
-
(2007)
BMC Bioinformatics
, vol.8
, pp. 438-450
-
-
Caragea, C.1
Sinapov, J.2
Silvescu, A.3
Dobbs, D.4
Honavar, V.5
-
18
-
-
70449371969
-
AESNB: Active example selection with näive bayes classifier for learning from imbalanced biomedical data
-
M.S. Lee, J.-K. Rhee, B.-H. Kim, and B.-T. Zhang, "AESNB: Active Example Selection with Näive Bayes Classifier for Learning from Imbalanced Biomedical Data," Proc. IEEE Int'l Conf. Bioinformatics and Bioeng., pp. 15-21, 2009.
-
(2009)
Proc. IEEE Int'l Conf. Bioinformatics and Bioeng.
, pp. 15-21
-
-
Lee, M.S.1
Rhee, J.-K.2
Kim, B.-H.3
Zhang, B.-T.4
-
19
-
-
0032645080
-
An empirical comparison of voting classification 37 algorithms: Bagging, boosting, and variants
-
E. Bauer and R. Kohavi, "An Empirical Comparison of Voting Classification 37 Algorithms: Bagging, Boosting, and Variants," Machine Learning, vol. 36, nos. 1/2, pp. 105-139, 1999.
-
(1999)
Machine Learning
, vol.36
, Issue.1-2
, pp. 105-139
-
-
Bauer, E.1
Kohavi, R.2
-
20
-
-
0034499376
-
A note on the utility of incremental learning
-
Dec.
-
C. Giraud-Carrier, "A Note on the Utility of Incremental Learning," AI Comm., vol. 13, no. 4, pp. 215-223, Dec. 2000.
-
(2000)
AI Comm.
, vol.13
, Issue.4
, pp. 215-223
-
-
Giraud-Carrier, C.1
-
21
-
-
0000735610
-
Operations for learning with graphical models
-
W.L. Buntine, "Operations for Learning with Graphical Models," J. Artificial Intelligence Research, vol. 2, pp. 159-225, 1994.
-
(1994)
J. Artificial Intelligence Research
, vol.2
, pp. 159-225
-
-
Buntine, W.L.1
-
23
-
-
0033569406
-
Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring
-
T.R. Golub, D.K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J.P. Mesirov, H. Coller, M.L. Loh, J.R. Downing, M.A. Caligiuri, C.D. Bloomfield, and E.S. Lander, "Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring," Science, vol. 286, pp. 531-537, 1999.
-
(1999)
Science
, vol.286
, pp. 531-537
-
-
Golub, T.R.1
Slonim, D.K.2
Tamayo, P.3
Huard, C.4
Gaasenbeek, M.5
Mesirov, J.P.6
Coller, H.7
Loh, M.L.8
Downing, J.R.9
Caligiuri, M.A.10
Bloomfield, C.D.11
Lander, E.S.12
-
24
-
-
0020748239
-
Computer-intensive methods in statistics
-
P. Diaconis and B. Efron, "Computer-Intensive Methods in Statistics," Scientific Am., vol. 248, pp. 116-128, 1983.
-
(1983)
Scientific Am.
, vol.248
, pp. 116-128
-
-
Diaconis, P.1
Efron, B.2
-
25
-
-
0001929348
-
Assistant-86: A knowledge elicitation tool for sophisticated users
-
I. Bratko and N. Lavrac, eds. Sigma Press
-
G. Cestnik, I. Konenenko, and I. Bratko, "Assistant-86: A Knowledge Elicitation Tool for Sophisticated Users," Progress in Machine Learning, I. Bratko and N. Lavrac, eds., pp. 31-45, Sigma Press, 1987.
-
(1987)
Progress in Machine Learning
, pp. 31-45
-
-
Cestnik, G.1
Konenenko, I.2
Bratko, I.3
-
26
-
-
34447507896
-
Exploiting nonlinear recurrence and fractal scaling properties for voice disorder detection
-
June
-
M.A. Little, P.E. McSharry, S.J. Roberts, D.A.E. Costello, and I.M. Moroz, "Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection," BioMedical Eng. OnLine, vol. 6, no. 23, pp. 23-42, June 2007.
-
(2007)
BioMedical Eng. OnLine
, vol.6
, Issue.23
, pp. 23-42
-
-
Little, M.A.1
McSharry, P.E.2
Roberts, S.J.3
Costello, D.A.E.4
Moroz, I.M.5
-
27
-
-
0024111497
-
Using the adap learning algorithm to forecast the onset of diabetes mellitus
-
J.W. Smith, J.E. Everhart, W.C. Dickson, W.C. Knowler, and R.S. Johannes, "Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus," Proc. Symp. Computer Applications and Medical Care, pp. 261-265, 1988.
-
(1988)
Proc. Symp. Computer Applications and Medical Care
, pp. 261-265
-
-
Smith, J.W.1
Everhart, J.E.2
Dickson, W.C.3
Knowler, W.C.4
Johannes, R.S.5
-
28
-
-
85043507102
-
An inductive learning approach to prognostic prediction
-
W.N. Street, O.L. Mangasarian, and W.H. Wolberg, "An Inductive Learning Approach to Prognostic Prediction," Proc. Int'l Conf. Machine Learning, pp. 522-530, 1995.
-
(1995)
Proc. Int'l Conf. Machine Learning
, pp. 522-530
-
-
Street, W.N.1
Mangasarian, O.L.2
Wolberg, W.H.3
|