-
2
-
-
50249118617
-
Genetic learning of membership functions for mining fuzzy association rules
-
Rafael Alcalá, Jesús Alcalá-Fdez, M.J. Gacto, and Francisco Herrera. Genetic learning of membership functions for mining fuzzy association rules. IEEE International Conference on Fuzzy Systems, 1:1538-1543, 2007.
-
(2007)
IEEE International Conference on Fuzzy Systems
, vol.1
, pp. 1538-1543
-
-
Alcalá, R.1
Alcalá-Fdez, J.2
Gacto, M.J.3
Herrera, F.4
-
4
-
-
0037860947
-
A clustering algorithm with genetically optimized membership functions for fuzzy association rules mining
-
M. Kaya and R. Alhajj. A clustering algorithm with genetically optimized membership functions for fuzzy association rules mining. 12th IEEE International Conference on Fuzzy Systems, 2:881-886, 2003.
-
(2003)
12th IEEE International Conference on Fuzzy Systems
, vol.2
, pp. 881-886
-
-
Kaya, M.1
Alhajj, R.2
-
6
-
-
0000810783
-
Fuzzy clustering analysis for optimizing membership functions
-
M. S. Chen and S. W. Wang. Fuzzy clustering analysis for optimizing membership functions. Fuzzy Sets and Systems, 103:239-254, 1999.
-
(1999)
Fuzzy Sets and Systems
, vol.103
, pp. 239-254
-
-
Chen, M.S.1
Wang, S.W.2
-
8
-
-
0037448870
-
A fuzzy c-means variant for the generation of fuzzy term sets
-
T. Warren Liao, Aivars K. Celmins, and Robert J. Hammell. A fuzzy c-means variant for the generation of fuzzy term sets. Fuzzy Sets and Systems, 135:241-257, 2003.
-
(2003)
Fuzzy Sets and Systems
, vol.135
, pp. 241-257
-
-
Warren Liao, T.1
Celmins, A.K.2
Hammell, R.J.3
-
10
-
-
0027601884
-
Adaptive-network-based fuzzy inference systems
-
J.S. Jang. Adaptive-network-based fuzzy inference systems. IEEE Trans. on SMC, 23:665-685, 1993.
-
(1993)
IEEE Trans. on SMC
, vol.23
, pp. 665-685
-
-
Jang, J.S.1
-
11
-
-
33745136405
-
A GA-based fuzzy mining approach to achieve a trade-off between number of rules and suitability of membership functions
-
Tzung-Pei Hong, Chun-Hao Chen, Yu-Lung Wu, and Yeong-Chyi Lee. A GA-based fuzzy mining approach to achieve a trade-off between number of rules and suitability of membership functions. Soft Computing, 10(11):1091-1101, 2006.
-
(2006)
Soft Computing
, vol.10
, Issue.11
, pp. 1091-1101
-
-
Hong, T.-P.1
Chen, C.-H.2
Wu, Y.-L.3
Lee, Y.-C.4
-
12
-
-
84902156141
-
Neuro fuzzy systems: State-of-the-art modeling techniques
-
Ajith Abraham. Neuro fuzzy systems: State-of-the-art modeling techniques. Lec. Notes in CS, 2084:269-276, 2001.
-
(2001)
Lec. Notes in CS
, vol.2084
, pp. 269-276
-
-
Abraham, A.1
-
14
-
-
0031077375
-
Automatically determine the membership function based on the maximum entropy principle
-
H. D. Cheng and Jim-Rong Chen. Automatically determine the membership function based on the maximum entropy principle. Information Sciences, 96(3-4):163-182, 1997.
-
(1997)
Information Sciences
, vol.96
, Issue.3-4
, pp. 163-182
-
-
Cheng, H.D.1
Chen, J.-R.2
-
17
-
-
33846098348
-
Fuzzy kappa for the agreement measure of fuzzy classifications
-
Weibei Dou, Yuan Ren, Qian Wu, Su Ruan, Yanping Chen, Daniel Bloyet, and Jean-Marc Constans. Fuzzy kappa for the agreement measure of fuzzy classifications. Neurocomputing, 70(4-6):726-734, 2007.
-
(2007)
Neurocomputing
, vol.70
, Issue.4-6
, pp. 726-734
-
-
Dou, W.1
Ren, Y.2
Wu, Q.3
Su, R.4
Chen, Y.5
Bloyet, D.6
Constans, J.-M.7
-
18
-
-
0027702852
-
Efficient fuzzy partition of pattern space for classification problems
-
Hisao Ishibuchi, Ken Nozaki, and Hideo Tanaka. Efficient fuzzy partition of pattern space for classification problems. Fuzzy Sets and Systems, 59(3):295-304, 1993.
-
(1993)
Fuzzy Sets and Systems
, vol.59
, Issue.3
, pp. 295-304
-
-
Ishibuchi, H.1
Nozaki, K.2
Tanaka, H.3
-
19
-
-
0022219988
-
A fuzzy k-nearest neighbor algorithm
-
J.M. Keller, M.R. Gray, and J.A. Given Jr. A fuzzy k-nearest neighbor algorithm. IEEE Transactions on Systems, Man, and Cybernetics, 15(4):580-585, 1985.
-
(1985)
IEEE Transactions on Systems, Man, and Cybernetics
, vol.15
, Issue.4
, pp. 580-585
-
-
Keller, J.M.1
Gray, M.R.2
Given Jr., J.A.3
-
20
-
-
0014534297
-
A new approach to clustering
-
Enrique H. Ruspini. A new approach to clustering. Information and Control, 15(1):22-32, 1969.
-
(1969)
Information and Control
, vol.15
, Issue.1
, pp. 22-32
-
-
Ruspini, E.H.1
-
22
-
-
0027580356
-
Very simple classification rules perform well on most commonly used datasets
-
Robert C. Holte. Very simple classification rules perform well on most commonly used datasets. Machine Learning, 11(1):63-90, 1993.
-
(1993)
Machine Learning
, vol.11
, Issue.1
, pp. 63-90
-
-
Holte, R.C.1
-
23
-
-
0346076783
-
The WM method completed: A flexible fuzzy system approach to data mining
-
L. Wang. The WM method completed: a flexible fuzzy system approach to data mining. IEEE International Conference on Fuzzy Systems, 11:768-782, 2003.
-
(2003)
IEEE International Conference on Fuzzy Systems
, vol.11
, pp. 768-782
-
-
Wang, L.1
-
24
-
-
29644438050
-
Statistical comparison of classifiers over multiple data sets
-
Janez Demšar. Statistical comparison of classifiers over multiple data sets. Journal of Machine Learning Research, 7(1):1-30, 2006.
-
(2006)
Journal of Machine Learning Research
, vol.7
, Issue.1
, pp. 1-30
-
-
Demšar, J.1
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