-
1
-
-
0036080160
-
Bagging boosting and the random subspace method for linear classifiers
-
Skurichina M, Duin RPW (2002) Bagging boosting and the random subspace method for linear classifiers. Pattern Anal Appl 5:121-135
-
(2002)
Pattern Anal Appl
, vol.5
, pp. 121-135
-
-
Skurichina, M.1
Duin, R.P.W.2
-
2
-
-
0030211964
-
Bagging predictors
-
Breiman L (1996) Bagging predictors. Mach Learn 24:123-140
-
(1996)
Mach Learn
, vol.24
, pp. 123-140
-
-
Breiman, L.1
-
3
-
-
0032645080
-
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
-
Bauer E, Kohavi R (1999) An empirical comparison of voting classification algorithms: bagging, boosting, and variants. Mach Learn 36:105-142
-
(1999)
Mach Learn
, vol.36
, pp. 105-142
-
-
Bauer, E.1
Kohavi, R.2
-
5
-
-
0001087620
-
Logistic regression, AdaBoost and Bregman distances
-
Palo Alto, California, June/July 2000
-
Collins M, Schapire RE, Singer Y (2000) Logistic regression, AdaBoost and Bregman distances. In: Proceedings of the 13th annual conference on computational learning theory, Palo Alto, California, June/July 2000, pp 158-169
-
(2000)
Proceedings of the 13th Annual Conference on Computational Learning Theory
, pp. 158-169
-
-
Collins, M.1
Schapire, R.E.2
Singer, Y.3
-
6
-
-
10444235601
-
-
Technical report, School of Informatics, University of Wales, Bangor, UK
-
Whitaker CJ, Kuncheva LI (2003) Examining the relationship between majority vote accuracy and diversity in bagging and boosting. Technical report, School of Informatics, University of Wales, Bangor, UK
-
(2003)
Examining the Relationship between Majority Vote Accuracy and Diversity in Bagging and Boosting
-
-
Whitaker, C.J.1
Kuncheva, L.I.2
-
7
-
-
85054435084
-
Neural network ensembles, cross validation, and active learning
-
Tesauro G, Touretzky D, Leen T (eds) MIT Press, Cambridge, Massachusetts
-
Krogh A, Vedelsby J (1995) Neural network ensembles, cross validation, and active learning. In: Tesauro G, Touretzky D, Leen T (eds) Advances in neural information processing systems, vol 7. MIT Press, Cambridge, Massachusetts, pp 231-238
-
(1995)
Advances in Neural Information Processing Systems
, vol.7
, pp. 231-238
-
-
Krogh, A.1
Vedelsby, J.2
-
8
-
-
0000551189
-
Popular ensemble methods: An empirical study
-
Opitz D, Maclin R (1999) Popular ensemble methods: an empirical study. J Artif Intell Res 11:169-198
-
(1999)
J Artif Intell Res
, vol.11
, pp. 169-198
-
-
Opitz, D.1
Maclin, R.2
-
9
-
-
84948152666
-
Using diversity in preparing ensembles of classifiers based on different feature subsets to minimize generalization error
-
Springer, Berlin Heidelberg New York
-
Zenobi G, Cunningham P (2001) Using diversity in preparing ensembles of classifiers based on different feature subsets to minimize generalization error. Lecture notes in computer science, Springer, Berlin Heidelberg New York, p 2167
-
(2001)
Lecture Notes in Computer Science
, pp. 2167
-
-
Zenobi, G.1
Cunningham, P.2
-
10
-
-
84880832861
-
Constructing diverse classifier ensembles using artificial training examples
-
Acapulco, Mexico, August 2003
-
Melville P, Mooney RJ (2003) Constructing diverse classifier ensembles using artificial training examples. In: Proceedings of the 18th international joint conference on artificial intelligence (IJCAI 2003), Acapulco, Mexico, August 2003, pp 505-510
-
(2003)
Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI 2003)
, pp. 505-510
-
-
Melville, P.1
Mooney, R.J.2
-
11
-
-
0036833267
-
Plurality voting based multiple classifier systems: Statistically independent with respect to dependent classifier sets
-
Demirekler M, Altinçay H (2002) Plurality voting based multiple classifier systems: statistically independent with respect to dependent classifier sets. Pattern Recogn 35(11):2365-2379
-
(2002)
Pattern Recogn
, vol.35
, Issue.11
, pp. 2365-2379
-
-
Demirekler, M.1
Altinçay, H.2
-
12
-
-
0035420134
-
Design of effective neural network ensembles for image classification purposes
-
Giacinto G, Roli F (2001) Design of effective neural network ensembles for image classification purposes. Image Vision Comput 19(9-10):669-707
-
(2001)
Image Vision Comput
, vol.19
, Issue.9-10
, pp. 669-707
-
-
Giacinto, G.1
Roli, F.2
-
13
-
-
0037403516
-
Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
-
Kuncheva LI, Whitaker CJ (2003) Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51:181-207
-
(2003)
Mach Learn
, vol.51
, pp. 181-207
-
-
Kuncheva, L.I.1
Whitaker, C.J.2
-
15
-
-
84860086818
-
Classifier selection for majority voting
-
More information to appear
-
Ruta D, Gabrys B (2004) Classifier selection for majority voting. More information at http://cis.paisley.ac.uk/ruta-c10/publications.htm. Inform Fusion J (to appear)
-
(2004)
Inform Fusion J
-
-
Ruta, D.1
Gabrys, B.2
-
16
-
-
0030356238
-
Actively searching for an effective neural-network ensemble
-
Opitz DW, Shavlik JW (1996) Actively searching for an effective neural-network ensemble. Connect Sci 8(3/4):337-353
-
(1996)
Connect Sci
, vol.8
, Issue.3-4
, pp. 337-353
-
-
Opitz, D.W.1
Shavlik, J.W.2
-
17
-
-
0034164230
-
Additive logistic regression: A statistical view of boosting
-
Friedman J, Hastie T, Tibshirani R (2000) Additive logistic regression: a statistical view of boosting. Ann Stat 28(2):337-374
-
(2000)
Ann Stat
, vol.28
, Issue.2
, pp. 337-374
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
19
-
-
0031171679
-
Optimal linear combinations of neural networks
-
Hashem S (1997) Optimal linear combinations of neural networks. Neural Netw 10(4):599-614
-
(1997)
Neural Netw
, vol.10
, Issue.4
, pp. 599-614
-
-
Hashem, S.1
-
20
-
-
0002978642
-
Experiments with a new boosting algorithm
-
Bari, Italy, July 1996. Morgan Kauffmann
-
Freund Y, Schapire RE (1996) Experiments with a new boosting algorithm. In: Proceedings of the 13th international conference on machine learning (ML'96), Bari, Italy, July 1996. Morgan Kauffmann, pp 148-156
-
(1996)
Proceedings of the 13th International Conference on Machine Learning (ML'96)
, pp. 148-156
-
-
Freund, Y.1
Schapire, R.E.2
-
21
-
-
0032139235
-
The random subspace method for constructing decision forests
-
Ho TK (1998) The random subspace method for constructing decision forests. IEEE Trans Pattern Anal Machine Intell 20(8):832-844
-
(1998)
IEEE Trans Pattern Anal Machine Intell
, vol.20
, Issue.8
, pp. 832-844
-
-
Ho, T.K.1
-
22
-
-
0002338687
-
A genetic algorithm tutorial
-
Whitley D (1994) A genetic algorithm tutorial. Stat Comput 4:65-85
-
(1994)
Stat Comput
, vol.4
, pp. 65-85
-
-
Whitley, D.1
-
24
-
-
0034314744
-
Designing classifier fusion systems by genetic algorithms
-
Kuncheva LI, Jain LC (2000) Designing classifier fusion systems by genetic algorithms. IEEE Trans Evol Comput 4(4):327-336
-
(2000)
IEEE Trans Evol Comput
, vol.4
, Issue.4
, pp. 327-336
-
-
Kuncheva, L.I.1
Jain, L.C.2
-
25
-
-
84956978205
-
Genetic algorithms for multi-classifier system configuration: A case study in character recognition
-
Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Springer, Berlin Heidelberg New York
-
Sirlantzis K, Fairhurst MC, Hoque S (2001) Genetic algorithms for multi-classifier system configuration: a case study in character recognition. In: Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Lecture notes in computer science. Springer, Berlin Heidelberg New York, pp 99-108
-
(2001)
Lecture Notes in Computer Science
, pp. 99-108
-
-
Sirlantzis, K.1
Fairhurst, M.C.2
Hoque, S.3
-
26
-
-
0029373189
-
Optimal combinations of pattern classifiers
-
Lam L, Suen CY (1995) Optimal combinations of pattern classifiers. Pattern Recogn Lett 16:945-954
-
(1995)
Pattern Recogn Lett
, vol.16
, pp. 945-954
-
-
Lam, L.1
Suen, C.Y.2
-
27
-
-
84956988905
-
Genetic algorithms for multi-classifier system configuration: A case study in character recognition
-
Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Springer, Berlin Heidelberg New York
-
Ruta D, Gabrys B (2001) Genetic algorithms for multi-classifier system configuration: a case study in character recognition. In: Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Lecture notes in computer science, Springer, Berlin Heidelberg New York, pp 399-408
-
(2001)
Lecture Notes in Computer Science
, pp. 399-408
-
-
Ruta, D.1
Gabrys, B.2
-
28
-
-
0012987265
-
A genetic algorithm approach for creating neural network ensembles
-
Sharkey AJC (ed) Springer, Berlin Heidelberg New York
-
Opitz D, Shavlik J (1999) A genetic algorithm approach for creating neural network ensembles. In: Sharkey AJC (ed) Combining artificial neural nets. Springer, Berlin Heidelberg New York, pp 79-99
-
(1999)
Combining Artificial Neural Nets
, pp. 79-99
-
-
Opitz, D.1
Shavlik, J.2
-
29
-
-
0033208087
-
Pruning boosted classifiers with a real valued genetic algorithm
-
Thompson S (1999) Pruning boosted classifiers with a real valued genetic algorithm. Knowl-Based Syst 12:277-284
-
(1999)
Knowl-Based Syst
, vol.12
, pp. 277-284
-
-
Thompson, S.1
-
30
-
-
0036567392
-
Ensembling neural networks: Many could be better than all
-
Zhou Z, Wu J, Tang W (2002) Ensembling neural networks: many could be better than all. Artif Intell 137:239-263
-
(2002)
Artif Intell
, vol.137
, pp. 239-263
-
-
Zhou, Z.1
Wu, J.2
Tang, W.3
-
31
-
-
84984302791
-
Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection
-
Leardi R (1994) Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection. J Chemometr 8:65-79
-
(1994)
J Chemometr
, vol.8
, pp. 65-79
-
-
Leardi, R.1
-
32
-
-
0024895461
-
A note on genetic algorithms for large-scale feature selection
-
Siedlecki W, Sklansky J (1989) A note on genetic algorithms for large-scale feature selection. Pattern Recogn Lett 10:335-347
-
(1989)
Pattern Recogn Lett
, vol.10
, pp. 335-347
-
-
Siedlecki, W.1
Sklansky, J.2
-
33
-
-
0032021555
-
On combining classifiers
-
Kittler J, Hatef M, Duin R, Matas J (1998) On combining classifiers. IEEE Trans Pattern Anal Machine Intell 20(3):226-239
-
(1998)
IEEE Trans Pattern Anal Machine Intell
, vol.20
, Issue.3
, pp. 226-239
-
-
Kittler, J.1
Hatef, M.2
Duin, R.3
Matas, J.4
-
34
-
-
84867038939
-
Experiments with classifier combining rules
-
Kittler J, Roli F (eds) Proceedings of the 1st international workshop on multiple classifier systems (MCS 2000), Sardinia, Italy, June 2000. Springer, Berlin Heidelberg New York
-
Duin RPW, Tax DMJ (2000) Experiments with classifier combining rules. In: Kittler J, Roli F (eds) Proceedings of the 1st international workshop on multiple classifier systems (MCS 2000), Sardinia, Italy, June 2000. Lecture notes in computer science, Springer, Berlin Heidelberg New York, pp 16-29
-
(2000)
Lecture Notes in Computer Science
, pp. 16-29
-
-
Duin, R.P.W.1
Tax, D.M.J.2
-
35
-
-
84947608948
-
Generating classifier ensembles from multiple prototypes and its application to handwriting recognition
-
Proceedings of the 3rd international workshop on multiple classifier systems (MCS2002), Cagliari, Italy, June 2002. Springer, Berlin Heidelberg New York
-
Gunter S, Bunke H (2002) Generating classifier ensembles from multiple prototypes and its application to handwriting recognition. In: Proceedings of the 3rd international workshop on multiple classifier systems (MCS2002), Cagliari, Italy, June 2002. Lecture notes in computer science, Springer, Berlin Heidelberg New York, pp 179-188
-
(2002)
Lecture Notes in Computer Science
, pp. 179-188
-
-
Gunter, S.1
Bunke, H.2
-
37
-
-
84956994921
-
Methods for designing multiple classifier systems
-
Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Springer, Berlin Heidelberg New York
-
Roli F, Giacinto G, Vernazza G (2001) Methods for designing multiple classifier systems. In: Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems (MCS 2001), Cambridge, UK, July 2001. Lecture notes in computer science, Springer, Berlin Heidelberg New York, pp 78-87
-
(2001)
Lecture Notes in Computer Science
, pp. 78-87
-
-
Roli, F.1
Giacinto, G.2
Vernazza, G.3
-
38
-
-
0033185714
-
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
-
Kalyanmoy Deb (1999) Multi-objective genetic algorithms: problem difficulties and construction of test problems. Evol Comput 7(3):205-230
-
(1999)
Evol Comput
, vol.7
, Issue.3
, pp. 205-230
-
-
|