-
3
-
-
0032026327
-
Machine learning from examples: Inductive and Lazy methods
-
Lopez, R.M. and Armengol, E.. Machine learning from examples: Inductive and Lazy methods. Data & Knowledge Engineering 25 (1998) 99-123.
-
(1998)
Data & Knowledge Engineering
, vol.25
, pp. 99-123
-
-
Lopez, R.M.1
Armengol, E.2
-
4
-
-
0011441842
-
The nearest neighbor rule and the reduction of the training sample size
-
Castellon, España
-
Barandela, R. et al., The nearest neighbor rule and the reduction of the training sample size. Proceedings 9th Symposium on Pattern Recognition and Image Analysis, 1, 103-108, Castellon, España, 2001.
-
(2001)
Proceedings 9th Symposium on Pattern Recognition and Image Analysis
, vol.1
, pp. 103-108
-
-
Barandela, R.1
-
6
-
-
84995347371
-
Myths about Rough Set Theory
-
nov
-
Koczkodaj, W.W. et al. Myths about Rough Set Theory. Comm. of the ACM, vol. 41, no. 11, nov. 1998.
-
(1998)
Comm. of the ACM
, vol.41
, Issue.11
-
-
Koczkodaj, W.W.1
-
7
-
-
33846985485
-
-
Komorowski, J. et al. A Rough set perspective on Data and Knowledge. In The Handbook of Data mining and Knowledge discovery, Klosgen, W. and Zytkow, J. (Eds). Oxford University Press, 1999.
-
Komorowski, J. et al. A Rough set perspective on Data and Knowledge. In The Handbook of Data mining and Knowledge discovery, Klosgen, W. and Zytkow, J. (Eds). Oxford University Press, 1999.
-
-
-
-
9
-
-
0035254283
-
Rough sets theory for multicriteria decision analysis
-
Greco, S. Et al. Rough sets theory for multicriteria decision analysis. European Journal of Operational Research 129, pp. 1-47, 2001.
-
(2001)
European Journal of Operational Research
, vol.129
, pp. 1-47
-
-
Greco, S.1
Et al.2
-
10
-
-
0036738810
-
Web mining in Soft Computing framework: Relevance, State of the art and Future Directions
-
Pal, S.K. et al. Web mining in Soft Computing framework: Relevance, State of the art and Future Directions. IEEE Transactions on Neural Networks, 2002.
-
(2002)
IEEE Transactions on Neural Networks
-
-
Pal, S.K.1
-
11
-
-
0001268347
-
Rosetta: A rough set toolkit for analysis of data
-
Durham, NC, USA, march 1-5
-
Ohrn, A. and Komorowski, J.. Rosetta: A rough set toolkit for analysis of data. In Proc. Third Int. Join Conference on Information Science, Durham, NC, USA, march 1-5, vol. 3, pp. 403-407. 1997.
-
(1997)
Proc. Third Int. Join Conference on Information Science
, vol.3
, pp. 403-407
-
-
Ohrn, A.1
Komorowski, J.2
-
12
-
-
33846960017
-
-
Ohrn, A, ROSETTA Technical Reference Manual. Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway
-
Ohrn, A.. ROSETTA Technical Reference Manual. Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway.
-
-
-
-
13
-
-
84947758926
-
ROSE- Software implementation of the Rough Set Theory
-
Polkowski, L. and Skowron, A, Eds, Berlin pp
-
Predki, B. et al. ROSE- Software implementation of the Rough Set Theory. In Polkowski, L. and Skowron, A. (Eds) Rough Sets and Current Trends in Computing, Proceedings of the RSCTC98 Conference. Lectures Notes in Artificial Intelligence vol. 1424, Berlin pp. 605-608.
-
Rough Sets and Current Trends in Computing, Proceedings of the RSCTC98 Conference. Lectures Notes in Artificial Intelligence
, vol.1424
, pp. 605-608
-
-
Predki, B.1
-
15
-
-
0003144494
-
Rough Sets: A tutorial
-
Pal, S.K. and Skowron, A, Eds, Springer, pp
-
Komorowski, J., Pawlak, Z. et al. Rough Sets: A tutorial. In Pal, S.K. and Skowron, A. (Eds) Rough Fuzzy Hybridization: A new trend in decision-making. Springer, pp. 3-98. 1999.
-
(1999)
Rough Fuzzy Hybridization: A new trend in decision-making
, pp. 3-98
-
-
Komorowski, J.1
Pawlak, Z.2
-
17
-
-
0037120630
-
Economic and financial prediction using rough set model
-
Tay, F.E. and Shen, L.. Economic and financial prediction using rough set model. European Journal of Operational Research 141, pp. 641-659. 2002.
-
(2002)
European Journal of Operational Research
, vol.141
, pp. 641-659
-
-
Tay, F.E.1
Shen, L.2
-
18
-
-
0016569790
-
An Algorithm for a Selective Nearest Neighbor Decision Rule
-
November, pp
-
Ritter, G. L., Woodruff, H. B., Lowry, S. R. and Isenhour, T. L. An Algorithm for a Selective Nearest Neighbor Decision Rule. IEEE Transactions on Information Theory, 21-6, November, pp. 665-669. 1975.
-
(1975)
IEEE Transactions on Information Theory, 21-6
, pp. 665-669
-
-
Ritter, G.L.1
Woodruff, H.B.2
Lowry, S.R.3
Isenhour, T.L.4
-
19
-
-
0001920729
-
Similarity Metric Learning for a Variable-Kernel Classifier
-
Lowe, David G.. Similarity Metric Learning for a Variable-Kernel Classifier. Neural Computation., 7-1, pp. 72-85. 1995.
-
(1995)
Neural Computation
, vol.7 -1
, pp. 72-85
-
-
Lowe1
David, G.2
-
20
-
-
0343081513
-
Randall and Martinez, Tony R. Reduction Techniques for Instance-Based Learning Algorithms
-
Computer Science Department, Brigham Young University. USA
-
Wilson, Randall and Martinez, Tony R. Reduction Techniques for Instance-Based Learning Algorithms. Machine Learning, 38:257-286. Computer Science Department, Brigham Young University. USA 2000.
-
(2000)
Machine Learning
, vol.38
, pp. 257-286
-
-
Wilson1
-
24
-
-
33846964373
-
Correcting the Training Data
-
Published in, D. Chen and X. Cheng eds, Kluwer
-
Barandela, R., Gasca, E., and Alejo, R., Correcting the Training Data. Published in "Pattern Recognition and String Matching", D. Chen and X. Cheng (eds.), Kluwer, 2002.
-
(2002)
Pattern Recognition and String Matching
-
-
Barandela, R.1
Gasca, E.2
Alejo, R.3
-
26
-
-
33846986658
-
-
Thesis. Department of Computer Science and Artificial Intelligence, Universidad de Granada, Spain. October
-
Cortijo, J.B.. Techniques of approximation II: Non parametric approximation. Thesis. Department of Computer Science and Artificial Intelligence, Universidad de Granada, Spain. October 2001.
-
(2001)
Techniques of approximation II: Non parametric approximation
-
-
Cortijo, J.B.1
-
27
-
-
0032048398
-
Computational methods for rough classification and discovery
-
Bell, D. and Guan, J.. Computational methods for rough classification and discovery. Journal of ASIS 49, 5, pp. 403-414, 1998.
-
(1998)
Journal of ASIS
, vol.49
, Issue.5
, pp. 403-414
-
-
Bell, D.1
Guan, J.2
-
28
-
-
0032046462
-
Feature selection and effective classifiers
-
Deogun, J.S. et al. Feature selection and effective classifiers. Journal of ASIS 49, 5, pp. 423-434. 1998.
-
(1998)
Journal of ASIS
, vol.49
, Issue.5
, pp. 423-434
-
-
Deogun, J.S.1
-
29
-
-
32444431723
-
A model based on Ant Colony System and Rough Set Theory to Feature Selection
-
June 25-29, Washington, USA
-
Bello, P.R. et al.. A model based on Ant Colony System and Rough Set Theory to Feature Selection. "Genetic and Evolutionary Conference (GECC005)". June 25-29, 2005. Washington, USA
-
(2005)
Genetic and Evolutionary Conference (GECC005)
-
-
Bello, P.R.1
-
30
-
-
21944436714
-
Using AGO and Rough Set Theory to Feature Selection
-
June, Lisbon, Portugal
-
Bello, P.R. et al. Using AGO and Rough Set Theory to Feature Selection. 6th WSEAS Evolutionary Computing Conference (EC05). June l6-18, 2005. Lisbon, Portugal.
-
(2005)
6th WSEAS Evolutionary Computing Conference (EC05)
-
-
Bello, P.R.1
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