-
1
-
-
0034324043
-
A formalism for relevance and its application in feature subset selection
-
doi:10.1023/A:1007612503587
-
Bell, D. A., & Wang, H. (2000). A formalism for relevance and its application in feature subset selection. Machine Learning, 41 (2), 175-195. doi:10.1023/A:1007612503587
-
(2000)
Machine Learning
, vol.41
, Issue.2
, pp. 175-195
-
-
Bell, D.A.1
Wang, H.2
-
2
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
doi:10.1016/S0004-3702 97 00063-5
-
Blum, A., & Langley, P. (1997). Selection of relevant features and examples in machine learning. Artificial Intelligence, 97 (1-2), 245-271. doi:10.1016/S0004-3702 (97) 00063-5
-
(1997)
Artificial Intelligence
, vol.97
, Issue.1-2
, pp. 245-271
-
-
Blum, A.1
Langley, P.2
-
4
-
-
0242302657
-
Consistency-based search in feature selection
-
doi:10.1016/S0004-3702 03 00079-1
-
Dash, M., & Liu, H. (2003). Consistency-based Search in Feature Selection. Artificial Intelligence, 151, 155-176. doi:10.1016/S0004-3702 (03) 00079-1
-
(2003)
Artificial Intelligence
, vol.151
, pp. 155-176
-
-
Dash, M.1
Liu, H.2
-
6
-
-
44649172031
-
Consistency based attribute reduction
-
In
-
Hu, Q. H., Zhao, H., Xie, Z. X., & Yu, D. R. (2007). Consistency Based Attribute Reduction. In. Proceedings of PAKDD, 2007, 96-107.
-
(2007)
Proceedings of PAKDD
, vol.2007
, pp. 96-107
-
-
Hu, Q.H.1
Zhao, H.2
Xie, Z.X.3
Yu, D.R.4
-
8
-
-
0028496468
-
Learning boolean concepts in the presence of many irrelevant features
-
doi:10.1016/0004-3702 94 90084-1
-
Hussein, A., & Thomas, G. D. (1994). Learning Boolean Concepts in the Presence of Many Irrelevant Features. Artificial Intelligence, 69 (1-2), 279-305. doi:10.1016/0004-3702 (94) 90084-1
-
(1994)
Artificial Intelligence
, vol.69
, Issue.1-2
, pp. 279-305
-
-
Hussein, A.1
Thomas, G.D.2
-
9
-
-
0029305145
-
Rough set reduction of attributes and their domains for neural networks
-
doi:10.1111/j.1467-8640.1995.tb00036.x
-
Jelonek, J., Krawiec, K., & Slowinski, R. (1995). Rough set reduction of attributes and their domains for neural networks. Computational Intelligence, 11, 339-347. doi:10.1111/j.1467-8640.1995.tb00036.x
-
(1995)
Computational Intelligence
, vol.11
, pp. 339-347
-
-
Jelonek, J.1
Krawiec, K.2
Slowinski, R.3
-
10
-
-
10944249572
-
Semantics-preserving dimensionality reduction: Rough and fuzzy-rough-based approaches
-
DOI 10.1109/TKDE.2004.96
-
Jensen, R., & Shen, Q. (2004). Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches. IEEE Transactions on Knowledge and Data Engineering, 16 (12), 1457-1471. doi:10.1109/TKDE.2004.96 (Pubitemid 40010921)
-
(2004)
IEEE Transactions on Knowledge and Data Engineering
, vol.16
, Issue.12
, pp. 1457-1471
-
-
Jensen, R.1
Shen, Q.2
-
14
-
-
0001225112
-
Neighborhood systems - A qualitative theory for fuzzy and rough sets
-
In Wang, P. Ed., Durham, NC: Duke University
-
Lin, T. Y. (1997). Neighborhood Systems-A Qualitative Theory for Fuzzy and Rough Sets. In Wang, P. (Ed.), Advances in Machine Intelligence and Soft Computing (Vol. 4, pp. 132-155). Durham, NC: Duke University.
-
(1997)
Advances in Machine Intelligence and Soft Computing
, vol.4
, pp. 132-155
-
-
Lin, T.Y.1
-
15
-
-
0000313665
-
Granular computing on binary relations I: Data mining and neighborhood systems
-
In Skowron, A., & Polkowski, L. Eds., Berlin: Physica Verlag
-
Lin, T. Y. (1998a). Granular Computing on Binary Relations I: Data Mining and Neighborhood Systems. In Skowron, A., & Polkowski, L. (Eds.), Rough Sets In Knowledge Discovery (pp. 107-121). Berlin: Physica Verlag.
-
(1998)
Rough Sets in Knowledge Discovery
, pp. 107-121
-
-
Lin, T.Y.1
-
16
-
-
0000053990
-
Granular computing on binary relations II: Rough set representations and belief functions
-
In Skowron, A., & Polkowski, L. Eds., Berlin: Physica Verlag
-
Lin, T. Y. (1998b). Granular Computing on Binary Relations II: Rough Set Representations and Belief Functions. In Skowron, A., & Polkowski, L. (Eds.), Rough Sets In Knowledge Discovery (pp. 121-140). Berlin: Physica Verlag.
-
(1998)
Rough Sets in Knowledge Discovery
, pp. 121-140
-
-
Lin, T.Y.1
-
18
-
-
69749112944
-
Quick hash based attribute reduction
-
Liu, Y., Xiong, R., & Chu, J. (2009). Quick Hash based Attribute Reduction. Chinese Journal of Computers, 32 (8), 1493-1499.
-
(2009)
Chinese Journal of Computers
, vol.32
, Issue.8
, pp. 1493-1499
-
-
Liu, Y.1
Xiong, R.2
Chu, J.3
-
21
-
-
0025565091
-
A modelling approach to feature selection
-
In
-
Sheinvald, J., Dom, B., & Niblack, W. (1990). A Modelling Approach to Feature Selection. In Proceedings of Tenth International Conference on Pattern Recognition (Vol. 1, pp. 535-539).
-
(1990)
Proceedings of Tenth International Conference on Pattern Recognition
, vol.1
, pp. 535-539
-
-
Sheinvald, J.1
Dom, B.2
Niblack, W.3
-
22
-
-
0037332841
-
Rough set methods in feature selection and recognition
-
doi:10.1016/S0167-8655 02 00196-4
-
Swiniarski, R. W., & Skowron, A. (2003). Rough set methods in feature selection and recognition. Pattern Recognition Letters, 24 (6), 833-849. doi:10.1016/S0167-8655 (02) 00196-4
-
(2003)
Pattern Recognition Letters
, vol.24
, Issue.6
, pp. 833-849
-
-
Swiniarski, R.W.1
Skowron, A.2
-
23
-
-
0035416447
-
Using rough sets with heuristics for feature selection
-
DOI 10.1023/A:1011219601502
-
Zhong, N., Dong, J., & Ohsuga, S. (2001). Using rough sets with heuristics for feature selection. Journal of Intelligent Information Systems, 16 (3), 199-214. doi:10.1023/A:1011219601502 (Pubitemid 32886812)
-
(2001)
Journal of Intelligent Information Systems
, vol.16
, Issue.3
, pp. 199-214
-
-
Zhong, N.1
Dong, J.2
Ohsuga, S.3
|