-
3
-
-
33646023117
-
An introduction to roc analysis
-
T. Fawcett, "An Introduction to ROC Analysis," Pattern Recognition Letters, vol. 27, pp. 861-874, 2006.
-
(2006)
Pattern Recognition Letters
, vol.27
, pp. 861-874
-
-
Fawcett, T.1
-
4
-
-
0024689801
-
A critical investigation of recall and precision as measures of retrieval system performance
-
V.V. Raghavan, G.S. Jung, and P. Bollmann, "A Critical Investigation of Recall and Precision as Measures of Retrieval System Performance," ACM Trans. Information Systems, vol. 7, pp. 205-229, 1989.
-
(1989)
ACM Trans. Information Systems
, vol.7
, pp. 205-229
-
-
Raghavan, V.V.1
Jung, G.S.2
Bollmann, P.3
-
5
-
-
33749249600
-
The relationship between precision-recall and roc curves
-
J. Davis and M. Goadrich, "The Relationship between Precision-Recall and ROC Curves," Proc. Int'l Conf. Machine Learning, pp. 233-240, 2006.
-
(2006)
Proc. Int'l Conf. Machine Learning
, pp. 233-240
-
-
Davis, J.1
Goadrich, M.2
-
6
-
-
0000259511
-
Approximate statistical tests for comparing supervised classification learning classifiers
-
T.G. Dietterich, "Approximate Statistical Tests for Comparing Supervised Classification Learning Classifiers," Neural Computation, vol. 10, pp. 1895-1923, 1998.
-
(1998)
Neural Computation
, vol.10
, pp. 1895-1923
-
-
Dietterich, T.G.1
-
7
-
-
0000359055
-
Combined 5 - 2 cv f test for comparing supervised classification learning classifiers
-
E. Alpaydin, "Combined 5 - 2 CV F test for Comparing Supervised Classification Learning Classifiers," Neural Computation, vol. 11, pp. 1975-1982, 1999.
-
(1999)
Neural Computation
, vol.11
, pp. 1975-1982
-
-
Alpaydin, E.1
-
8
-
-
0031536511
-
Improvements on cross-validation: The.632+ bootstrap method
-
B. Efron and R. Tibshirani, "Improvements on Cross-Validation: The.632+ Bootstrap Method," J. Am. Statistical Assoc., vol. 92, pp. 548-560, 1997.
-
(1997)
J. Am. Statistical Assoc
, vol.92
, pp. 548-560
-
-
Efron, B.1
Tibshirani, R.2
-
9
-
-
29644438050
-
Statistical comparisons of classifiers over multiple data sets
-
J. Demsar, "Statistical Comparisons of Classifiers over Multiple Data Sets," J. Machine Learning Research, vol. 7, pp. 1-30, 2006.
-
(2006)
J. Machine Learning Research
, vol.7
, pp. 1-30
-
-
Demsar, J.1
-
12
-
-
27144463192
-
On comparing classifiers: Pitfalls to avoid and a recommended approach
-
S.L. Salzberg, "On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach," Data Mining and Knowledge Discovery, vol. 1, pp. 317-328, 1997.
-
(1997)
Data Mining and Knowledge Discovery
, vol.1
, pp. 317-328
-
-
Salzberg, S.L.1
-
13
-
-
0042847140
-
Inference for the generalization error
-
C. Nadeau and Y. Bengio, "Inference for the Generalization Error," Machine Learning, vol. 52, pp. 239-281, 2003.
-
(2003)
Machine Learning
, vol.52
, pp. 239-281
-
-
Nadeau, C.1
Bengio, Y.2
-
14
-
-
33847708108
-
Estimating replicability of classifier learning experiments
-
R.R. Bouckaert, "Estimating Replicability of Classifier Learning Experiments," Proc. Int'l Conf. Machine Learning, pp. 15-22, 2004.
-
(2004)
Proc. Int'l Conf. Machine Learning
, pp. 15-22
-
-
Bouckaert, R.R.1
-
16
-
-
0020083498
-
The meaning and use of the area under a receiver operating characteristic (roc) curve
-
J.A. Hanley and B.J. McNeil, "The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve," Radiology, vol. 143, pp. 29-36, 1982.
-
(1982)
Radiology
, vol.143
, pp. 29-36
-
-
Hanley, J.A.1
McNeil, B.J.2
-
17
-
-
7044227562
-
Auc: A better measure than accuracy in comparing learning algorithms
-
C.X. Ling, J. Huang, and H. Zhang, "AUC: A Better Measure than Accuracy in Comparing Learning Algorithms," Proc. Int'l Joint Conf. Artificial Intelligence, pp. 329-341, 2004.
-
(2004)
Proc. Int'l Joint Conf. Artificial Intelligence
, pp. 329-341
-
-
Ling, C.X.1
Huang, J.2
Zhang, H.3
-
18
-
-
44649092482
-
Comparing naive bayes, decision trees, and svm with auc and accuracy
-
J. Huang, J. Lu, and C. Ling, "Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy," Proc. IEEE Int'l Conf. Data Mining, pp. 553-556, 2003.
-
(2003)
Proc. IEEE Int'l Conf. Data Mining
, pp. 553-556
-
-
Huang, J.1
Lu, J.2
Ling, C.3
-
19
-
-
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, pp. 1145-1159, 1997.
-
(1997)
Pattern Recognition
, vol.30
, pp. 1145-1159
-
-
Bradley, A.P.1
-
20
-
-
0020524559
-
A method of comparing the areas under receiver operating characteristic curves derived from the same cases
-
J.A. Hanley and B.J. McNeil, "A Method of Comparing the Areas under Receiver Operating Characteristic Curves Derived from the Same Cases," Radiology, vol. 148, pp. 839-843, 1983.
-
(1983)
Radiology
, vol.148
, pp. 839-843
-
-
Hanley, J.A.1
McNeil, B.J.2
-
22
-
-
66249133953
-
Examining the relative influence of familial, genetic, and environmental covariate information in flexible risk models
-
H.C. Bravo, G. Wahba, K.E. Lee, B.E.K. Klein, R. Klein, and S.K. Iyengar, "Examining the Relative Influence of Familial, Genetic, and Environmental Covariate Information in Flexible Risk Models," Proc. Nat'l Academy of Sciences USA, vol. 106, pp. 8128-8133, 2004.
-
(2004)
Proc. Nat'l Academy of Sciences USA
, vol.106
, pp. 8128-8133
-
-
Bravo, H.C.1
Wahba, G.2
Lee, K.E.3
Klein, B.E.K.4
Klein, R.5
Iyengar, S.K.6
-
23
-
-
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
-
24
-
-
77951964158
-
Small-sample precision of roc-related estimates
-
B. Hanczar, J. Hua, C. Sima, J. Weinstein, M. Bittner, and E.R. Dougherty, "Small-Sample Precision of Roc-Related Estimates," Bioinformatics, vol. 26, no. 6, pp. 822-830, 2010.
-
(2010)
Bioinformatics
, vol.26
, Issue.6
, pp. 822-830
-
-
Hanczar, B.1
Hua, J.2
Sima, C.3
Weinstein, J.4
Bittner, M.5
Dougherty, E.R.6
-
25
-
-
77952832818
-
A croc stronger than roc: Measuring, visualizing, and optimizing early retrieval
-
S.J. Swamidass, C.-A. Azencott, K. Daily, and P. Baldi, "A Croc Stronger than Roc: Measuring, Visualizing, and Optimizing Early Retrieval," Bioinformatics, vol. 26, no. 10, pp. 1348-1356, 2010.
-
(2010)
Bioinformatics
, vol.26
, Issue.10
, pp. 1348-1356
-
-
Swamidass, S.J.1
Azencott, C.-A.2
Daily, K.3
Baldi, P.4
-
26
-
-
60649086930
-
Comparison of four performance metrics for evaluating sampling techniques for low quality class-imbalanced data
-
A. Folleco, T.M. Khoshgoftaar, and A. Napolitano, "Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data," Proc. Int'l Conf. Machine Learning and Applications, pp. 153-158, 2008.
-
(2008)
Proc. Int'l Conf. Machine Learning and Applications
, pp. 153-158
-
-
Folleco, A.1
Khoshgoftaar, T.M.2
Napolitano, A.3
-
27
-
-
0030368635
-
Machine learning of user profiles: Representational issues
-
E. Bloedorn, I. Mani, and T.R. Macmillan, "Machine Learning of User Profiles: Representational Issues," Proc. Nat'l Conf. Artificial Intelligence, pp. 433-438, 1996.
-
(1996)
Proc. Nat'l Conf. Artificial Intelligence
, pp. 433-438
-
-
Bloedorn, E.1
Mani, I.2
Macmillan, T.R.3
-
28
-
-
34147120594
-
Precision-recall operating characteristic (p-roc) curves in imprecise environments
-
T.C.W. Landgrebe, P. Paclik, and R.P.W. Duin, "Precision-Recall Operating Characteristic (P-ROC) Curves in Imprecise Environments," Proc. Int'l Conf. Pattern Recognition, pp. 123-127, 2006.
-
(2006)
Proc. Int'l Conf. Pattern Recognition
, pp. 123-127
-
-
Landgrebe, T.C.W.1
Paclik, P.2
Duin, R.P.W.3
-
30
-
-
47849133262
-
The expected performance curve
-
S.B. Bengio, J. Marithoz, and M. Keller, "The Expected Performance Curve," Proc. Int'l Conf. Machine Learning, pp. 9-16, 2005.
-
(2005)
Proc. Int'l Conf. Machine Learning
, pp. 9-16
-
-
Bengio, S.B.1
Marithoz, J.2
Keller, M.3
-
31
-
-
33748991193
-
Cost curves: An improved method for visualizing classifier performance
-
Oct
-
C. Drummond and R.C. Holte, "Cost Curves: An Improved Method for Visualizing Classifier Performance," Machine Learning, vol. 65, no. 1, pp. 95-130, Oct. 2006.
-
(2006)
Machine Learning
, vol.65
, Issue.1
, pp. 95-130
-
-
Drummond, C.1
Holte, R.C.2
-
32
-
-
31544479266
-
Ordering and finding the best of k >2 supervised learning algorithms
-
Mar
-
O.T. Yildiz and E. Alpaydin, "Ordering and Finding the Best of K >2 Supervised Learning Algorithms," IEEE Trans. Pattern Analysis Machine Intelligence, vol. 28, no. 3, pp. 392-402, Mar. 2006.
-
(2006)
IEEE Trans. Pattern Analysis Machine Intelligence
, vol.28
, Issue.3
, pp. 392-402
-
-
Yildiz, O.T.1
Alpaydin, E.2
-
34
-
-
83655191921
-
Cost-conscious comparison of supervised learning algorithms over multiple data sets
-
A. Ulaş, O.T. Yildiz, and E. Alpaydin, "Cost-Conscious Comparison of Supervised Learning Algorithms over Multiple Data Sets," Pattern Recognition, vol. 45, pp. 1772-1781, 2012.
-
(2012)
Pattern Recognition
, vol.45
, pp. 1772-1781
-
-
Ulaş, A.1
Yildiz, O.T.2
Alpaydin, E.3
-
36
-
-
58149287952
-
An extension on " statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons,"
-
S. Garc'́a and F. Herrera, "An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for All Pairwise Comparisons," J. Machine Learning Research, vol. 9, pp. 2677-2694, 2008.
-
(2008)
J. Machine Learning Research
, vol.9
, pp. 2677-2694
-
-
Garća, S.1
Herrera, F.2
-
37
-
-
0002294347
-
A simple sequentially rejective multiple test procedure
-
S. Holm, "A Simple Sequentially Rejective Multiple Test Procedure," Scandinavian J. Statistics, vol. 6, pp. 65-70, 1979.
-
(1979)
Scandinavian J. Statistics
, vol.6
, pp. 65-70
-
-
Holm, S.1
-
38
-
-
84890829458
-
Modified sequentially rejective multiple test procedures
-
J.P. Shaffer, "Modified Sequentially Rejective Multiple Test Procedures," J. Am. Statistical Assoc., vol. 81, no. 395, pp. 826-831, 1986.
-
(1986)
J. Am. Statistical Assoc
, vol.81
, Issue.395
, pp. 826-831
-
-
Shaffer, J.P.1
-
39
-
-
0009038905
-
Improvements of general multiple test procedures for redundant systems of hypotheses
-
P. Bauer, G. Hommel, and E. Sonnemann, eds Springer
-
G. Bergmann and G. Hommel, "Improvements of General Multiple Test Procedures for Redundant Systems of Hypotheses," Multiple Hypotheses Testing, P. Bauer, G. Hommel, and E. Sonnemann, eds., pp. 100-115, Springer, 1988.
-
(1988)
Multiple Hypotheses Testing
, pp. 100-115
-
-
Bergmann, G.1
Hommel, G.2
-
40
-
-
83255194568
-
The rise and fall of supervised machine learning techniques
-
L.J. Jensen and A. Bateman, "The Rise and Fall of Supervised Machine Learning Techniques," Bioinformatics, vol. 27, no. 24, pp. 3331-3332, 2011.
-
(2011)
Bioinformatics
, vol.27
, Issue.24
, pp. 3331-3332
-
-
Jensen, L.J.1
Bateman, A.2
-
43
-
-
18644377870
-
Linear discriminant trees
-
O.T. Yildiz and E. Alpaydin, "Linear Discriminant Trees," Int'l J. Pattern Recognition and Artificial Intelligence, vol. 19, no. 3, pp. 323-353, 2005.
-
(2005)
Int'l J. Pattern Recognition and Artificial Intelligence
, vol.19
, Issue.3
, pp. 323-353
-
-
Yildiz, O.T.1
Alpaydin, E.2
-
44
-
-
0030333286
-
A generalized hidden markov model for the recognition of human genes in dna
-
D. Kulp, D. Haussler, M.G. Reese, and F.H. Eeckman, "A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA," Proc. Int'l Conf. Intelligent Systems for Molecular Biology, 1996.
-
(1996)
Proc. Int'l Conf. Intelligent Systems for Molecular Biology
-
-
Kulp, D.1
Haussler, D.2
Reese, M.G.3
Eeckman, F.H.4
-
45
-
-
15844413351
-
A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis
-
A. Statnikov, C. Aliferis, I. Tsamardinos, D. Hardin, and S. Levy, "A Comprehensive Evaluation of Multicategory Classification Methods for Microarray Gene Expression Cancer Diagnosis," Bioinformatics, vol. 21, pp. 631-643, 2005.
-
(2005)
Bioinformatics
, vol.21
, pp. 631-643
-
-
Statnikov, A.1
Aliferis, C.2
Tsamardinos, I.3
Hardin, D.4
Levy, S.5
-
46
-
-
77951972791
-
Cascleave: Towards more accurate prediction of caspase substrate cleavage sites
-
J. Song, H. Tan, H. Shen, K. Mahmood, S.E. Boyd, G.I. Webb, T. Akutsu, and J.C. Whisstock, "Cascleave: Towards More Accurate Prediction of Caspase Substrate Cleavage Sites," Bioinformatics, vol. 26, pp. 752-760, 2010.
-
(2010)
Bioinformatics
, vol.26
, pp. 752-760
-
-
Song, J.1
Tan, H.2
Shen, H.3
Mahmood, K.4
Boyd, S.E.5
Webb, G.I.6
Akutsu, T.7
Whisstock, J.C.8
-
47
-
-
79551655554
-
On position-specific scoring matrix for protein function prediction
-
Mar./Apr
-
J.C. Jeong, X. Lin, and X.-W. Chen, "On Position-Specific Scoring Matrix for Protein Function Prediction," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 2, pp. 308-315, Mar./Apr. 2011.
-
(2011)
IEEE/ACM Trans. Computational Biology and Bioinformatics
, vol.8
, Issue.2
, pp. 308-315
-
-
Jeong, J.C.1
Lin, X.2
Chen, X.-W.3
-
48
-
-
77955033518
-
Efficient learning of microbial genotype-phenotype association rules
-
N.J. MacDonald and R.G. Beiko, "Efficient Learning of Microbial Genotype-Phenotype Association Rules," Bioinformatics, vol. 26, pp. 1834-1840, 2010.
-
(2010)
Bioinformatics
, vol.26
, pp. 1834-1840
-
-
Macdonald, N.J.1
Beiko, R.G.2
-
49
-
-
79951780542
-
Multiclass classification of microarray data samples with a reduced number of genes
-
article 59
-
E. Tapia, L. Ornella, P. Bulacio, and L. Angelone, "Multiclass Classification of Microarray Data Samples with a Reduced Number of Genes," BMC Bioinformatics, vol. 12, article 59, 2011.
-
(2011)
BMC Bioinformatics
, vol.12
-
-
Tapia, E.1
Ornella, L.2
Bulacio, P.3
Angelone, L.4
-
50
-
-
76849086406
-
Feature selection for gene expression using model-based entropy
-
Jan.-Mar.
-
S. Zhu, D. Wang, K. Yu, T. Li, and Y. Gong, "Feature Selection for Gene Expression Using Model-Based Entropy," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 7, no. 1, pp. 25-36, Jan.-Mar. 2010.
-
(2010)
IEEE/ACM Trans. Computational Biology and Bioinformatics
, vol.7
, Issue.1
, pp. 25-36
-
-
Zhu, S.1
Wang, D.2
Yu, K.3
Li, T.4
Gong, Y.5
-
51
-
-
76849090053
-
Sparse support vector machines with lp penalty for biomarker identification
-
Jan.-Mar
-
Z. Liu, S. Lin, and M.T. Tan, "Sparse Support Vector Machines with lp Penalty for Biomarker Identification," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 7, no. 1, pp. 100-107, Jan.-Mar. 2010.
-
(2010)
IEEE/ACM Trans. Computational Biology and Bioinformatics
, vol.7
, Issue.1
, pp. 100-107
-
-
Liu, Z.1
Lin, S.2
Tan, M.T.3
|