-
1
-
-
0027621699
-
-
(USA) May
-
Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases, SIGMOD,Washington D.C. (USA), May 1993.
-
(1993)
Mining Association Rules between Sets of Items in Large Databases SIGMODWashington D.C
-
-
Agrawal, R.1
Imielinski, T.2
Swami, A.3
-
2
-
-
77949578752
-
-
September
-
Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules, International Conference on Very Large Data Bases, Santiago de Chile (Chile), September 1994.
-
(1994)
Fast Algorithms for Mining Association Rules, International Conference on Very Large Data Bases, Santiago de Chile (Chile)
-
-
Agrawal, R.1
Srikant, R.2
-
3
-
-
59649112625
-
Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms
-
Alcala-Fdez, J., Alcala, R., Gacto, M. J., Herrera, F.: Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms, Fuzzy Sets and Systems, 160(7), 2009, 905-921.
-
(2009)
Fuzzy Sets and Systems
, vol.160
, Issue.7
, pp. 905-921
-
-
Alcala-Fdez, J.1
Alcala, R.2
Gacto, M.J.3
Herrera, F.4
-
4
-
-
35248852487
-
Evolving multiple discretizations with adaptive intervals for a pittsburgh rule- based learning classifier system
-
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (E. Cantu-Paz, J. Foster, Eds.)
-
Bacardit, J., Garrell, J.-M.: Evolving Multiple Discretizations with Adaptive Intervals for a Pittsburgh Rule- Based Learning Classifier System, in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (E. Cantu-Paz, J. Foster, Eds.), vol.2724 of Lecture Notes in Computer Science, Springer, Heidelberg, 2003, 1818-1831.
-
(2003)
Lecture Notes in Computer Science, Springer, Heidelberg
, vol.2724
, pp. 1818-1831
-
-
Bacardit, J.1
Garrell, J.-M.2
-
5
-
-
38049170776
-
Improving the performance of a pittsburgh learning classifier system using a default rule
-
Learning Classifier Systems (T. Kovacs, X. Llor, K. Takadama, P. L. Lanzi, W. Stolzmann, , S. W. Wilson, Eds.)
-
Bacardit, J., Goldberg, D.-E., Butz, M.-V.: Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule, in: Learning Classifier Systems (T. Kovacs, X. Llor, K. Takadama, P. L. Lanzi, W. Stolzmann, , S. W. Wilson, Eds.), vol.4399 of Lecture Notes in Computer Science, Springer, Heidelberg, 2007, 291-307.
-
(2007)
Lecture Notes in Computer Science, Springer, Heidelberg
, vol.4399
, pp. 291-307
-
-
Bacardit, J.1
Goldberg, D.-E.2
Butz, M.-V.3
-
6
-
-
85011047355
-
A trie-based APRIORI implementation for mining frequent item sequences
-
Chicago, Illinois, USA, August
-
Bodon, F.: A trie-based APRIORI implementation for mining frequent item sequences, 1st International Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations, Chicago, Illinois, USA, August 2005.
-
(2005)
1st International Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations
-
-
Bodon, F.1
-
7
-
-
19544387826
-
Efficient implementations of apriori and éclat
-
CEUR Workshop Proc., Florida, USA
-
Borgelt, C.: Efficient Implementations of Apriori and Eclat, in: Workshop on Frequent Itemset Mining Implementations, vol.90, CEUR Workshop Proc., Florida, USA, 2003, 280-296.
-
(2003)
Workshop on Frequent Itemset Mining Implementations
, vol.90
, pp. 280-296
-
-
Borgelt, C.1
-
8
-
-
58049202911
-
A genetic-fuzzy mining approach for items with multiple minimum supports
-
Chen, C.-H., Hong, T.-P., Tseng, V. S., Lee, Y.-C.: A genetic-fuzzy mining approach for items with multiple minimum supports, Soft Computing, 13(5), 2008, 521-533.
-
(2008)
Soft Computing
, vol.13
, Issue.5
, pp. 521-533
-
-
Chen, C.-H.1
Hong, T.-P.2
Tseng, V.S.3
Lee, Y.-C.4
-
9
-
-
0003927095
-
-
World Scientific
-
Cord́on,O., Herrera, F., Hoffmann, F.,Magdalena, L.: GENETIC FUZZY SYSTEMS. Evolutionary tuning and learning of fuzzy knowledge bases. Advances in Fuzzy Systems - Applications and Theory, World Scientific, 2001.
-
(2001)
GENETIC FUZZY SYSTEMS. Evolutionary Tuning and Learning of Fuzzy Knowledge Bases. Advances in Fuzzy Systems - Applications and Theory
-
-
Cord́on, O.1
Herrera, F.2
Hoffmann, F.3
Magdalena, L.4
-
11
-
-
0242704414
-
-
Springer-Verlag New York, Inc., Secaucus, NJ, USA
-
Freitas, A. A.: Data Mining and Knowledge Discovery with Evolutionary Algorithms, Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2002.
-
(2002)
Data Mining and Knowledge Discovery with Evolutionary Algorithms
-
-
Freitas, A.A.1
-
12
-
-
0003722376
-
-
Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA
-
Goldberg, D. E.: Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1989.
-
(1989)
Genetic Algorithms in Search, Optimization and Machine Learning
-
-
Goldberg, D.E.1
-
13
-
-
0027696043
-
Competition-based induction of decision models from examples
-
Greene, D., Smith, S.: Competition-based induction of decision models from examples, Machine Learning, 13(2-3), 1993, 229-257.
-
(1993)
Machine Learning
, vol.13
, Issue.2-3
, pp. 229-257
-
-
Greene, D.1
Smith, S.2
-
14
-
-
0003963776
-
-
Kluwer Academic Publishers, Norwell, MA, USA
-
Grefenstette, J. J.: Genetic Algorithms for Machine Learning, Kluwer Academic Publishers, Norwell, MA, USA, 1994.
-
(1994)
Genetic Algorithms for Machine Learning
-
-
Grefenstette, J.J.1
-
15
-
-
0003585297
-
-
Second Edition, Morgan Kaufmann, San Fransisco
-
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Second Edition, Morgan Kaufmann, San Fransisco, 2006.
-
(2006)
Data Mining: Concepts and Techniques
-
-
Han, J.1
Kamber, M.2
-
16
-
-
2442449952
-
Mining frequent patterns without candidate generation: A frequent- pattern tree approach
-
Han, J., Pei, J., Yin, Y., Mao, R.: Mining Frequent Patterns without Candidate Generation: A Frequent- Pattern Tree Approach, Data Mining and Knowledge Discovery, 8(1), 2004, 53-87.
-
(2004)
Data Mining and Knowledge Discovery
, vol.8
, Issue.1
, pp. 53-87
-
-
Han, J.1
Pei, J.2
Yin, Y.3
Mao, R.4
-
17
-
-
50149096917
-
Genetic fuzzy systems: Taxonomy, current research trends and prospects
-
Herrera, F.: Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects, Evolutionary Intelligence, 1(1), 2008, 27-46.
-
(2008)
Evolutionary Intelligence
, vol.1
, Issue.1
, pp. 27-46
-
-
Herrera, F.1
-
18
-
-
0001666176
-
Cognitive systems based on adaptive algorithms
-
(D. Waterman, F. Hayes-Roth, Eds.) Academic Press, London
-
Holland, J., Reitman, J.: Cognitive systems based on adaptive algorithms, in: Patter-directed inference systems (D. Waterman, F. Hayes-Roth, Eds.), Academic Press, London, 1978, 1148-1158.
-
(1978)
Patter-directed Inference Systems
, pp. 1148-1158
-
-
Holland, J.1
Reitman, J.2
-
19
-
-
0003463297
-
-
MIT Press, Cambridge,MA, USA
-
Holland, J. H.: Adaptation in natural and artificial systems, MIT Press, Cambridge,MA, USA, 1975.
-
(1975)
Adaptation in Natural and Artificial Systems
-
-
Holland, J.H.1
-
20
-
-
42249089539
-
Genetic-fuzzy data mining with divide-and-conquer strategy
-
Hong, T.-P., Chen, C.-H., Lee, Y.-C., , Wu, Y.-L.: Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy, IEEE Transactions on Evolutionary Computation, 12(2), 2008, 252-265.
-
(2008)
IEEE Transactions on Evolutionary Computation
, vol.12
, Issue.2
, pp. 252-265
-
-
Hong, T.-P.1
Chen, C.-H.2
Lee, Y.-C.3
Wu, Y.-L.4
-
21
-
-
33750700010
-
-
Springer-Verlag New York, Inc., Secaucus, NJ, USA
-
Jain, L. C., Ghosh, A.: Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing), Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005.
-
(2005)
Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
-
-
Jain, L.C.1
Ghosh, A.2
-
22
-
-
33644667964
-
Evaluating the performance of cost-based discretization versus entropy- and error-based discretization
-
Janssens, D., Brijs, T., Vanhoof, K.,Wets, G.: Evaluating the performance of cost-based discretization versus entropy- and error-based discretization, Computers and Operations Research, 33(11), 2006, 3107-3123.
-
(2006)
Computers and Operations Research
, vol.33
, Issue.11
, pp. 3107-3123
-
-
Janssens, D.1
Brijs, T.2
Vanhoof, K.3
Wets, G.4
-
23
-
-
0027696338
-
Using genetic algorithms for concept learning
-
Jong, K. D., Spears, W., Gordon, D.: Using genetic algorithms for concept learning, Machine Learning, 13(2-3), 1993, 161-188.
-
(1993)
Machine Learning
, vol.13
, Issue.2-3
, pp. 161-188
-
-
Jong, K.D.1
Spears, W.2
Gordon, D.3
-
24
-
-
31144468507
-
Utilizing genetic algorithms to optimize membership functions for fuzzy weighted association rules mining
-
Kaya, M., Alhajj, R.: Utilizing Genetic Algorithms to Optimize Membership Functions for Fuzzy Weighted Association Rules Mining, Applied Intelligence, 24(1), 2006, 7-15.
-
(2006)
Applied Intelligence
, vol.24
, Issue.1
, pp. 7-15
-
-
Kaya, M.1
Alhajj, R.2
-
25
-
-
34047243825
-
A Hellinger-based discretization method for numerica attributes in classification learning
-
Lee, C.-H.: A Hellinger-based discretization method for numerica attributes in classification learning, Knowledge-Based Systems, 20(4), 2007, 419-425.
-
(2007)
Knowledge-Based Systems
, vol.20
, Issue.4
, pp. 419-425
-
-
Lee, C.-H.1
-
26
-
-
0141688369
-
Discretization: An enabling technique
-
Liu, H., Hussain, F., Tan, C., Dash,M.: Discretization: An Enabling Technique, DataMining and Knowledge Discovery, 6(4), 2002, 393-423.
-
(2002)
DataMining and Knowledge Discovery
, vol.6
, Issue.4
, pp. 393-423
-
-
Liu, H.1
Hussain, F.2
Tan, C.3
Dash, M.4
-
27
-
-
84945244688
-
Discovering numeric association rules via evolu-tionary algorithm
-
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (G. Rawlin, Ed.) Springer, Heidelberg
-
Mata, J., Alvarez, J., Riquelme, J.: Discovering Numeric Association Rules via Evolu-tionary Algorithm, in: Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (G. Rawlin, Ed.), vol.2336 of Lecture Notes in Computer Science, Springer, Heidelberg, 1991, 40-51.
-
(1991)
Lecture Notes in Computer Science
, vol.2336
, pp. 40-51
-
-
Mata, J.1
Alvarez, J.2
Riquelme, J.3
-
28
-
-
0005260330
-
Mining numeric association rules with genetic algorithms
-
Taipei, Taiwan, April
-
Mata, J., Alvarez, J., Riquelme, J.: Mining Numeric Association Rules with Genetic Algorithms, 5th International Conference on Artificial Neural Networks and Genetic Algorithms, Taipei, Taiwan, April 2001.
-
(2001)
5th International Conference on Artificial Neural Networks and Genetic Algorithms
-
-
Mata, J.1
Alvarez, J.2
Riquelme, J.3
-
29
-
-
0036038544
-
An evolutionary algorithm to discover numeric association rules
-
Madrid, Spain, March
-
Mata, J., Alvarez, J., Riquelme, J.: An Evolutionary Algorithm to Discover Numeric Association Rules, ACM Symposium on Applied Computing,Madrid, Spain, March 2002.
-
(2002)
ACM Symposium on Applied Computing
-
-
Mata, J.1
Alvarez, J.2
Riquelme, J.3
-
30
-
-
2142654791
-
-
Mladenic, D., Lavrac, N., Bohanec, M., Moyle, S., Eds. Kluwer Academic Publishers, Norwell, MA, USA
-
Mladenic, D., Lavrac, N., Bohanec, M., Moyle, S., Eds.: Data Mining and Decision Support: Integration and Collaboration, Kluwer Academic Publishers, Norwell, MA, USA, 2002.
-
(2002)
Data Mining and Decision Support: Integration and Collaboration
-
-
-
31
-
-
85052439689
-
-
Pal, S. K., Wang, P. P., Eds. CRC Press, Inc., Boca Raton, FL, USA
-
Pal, S. K., Wang, P. P., Eds.: Genetic Algorithms for Pattern Recognition, CRC Press, Inc., Boca Raton, FL, USA, 1996.
-
(1996)
Genetic Algorithms for Pattern Recognition
-
-
-
33
-
-
0030157416
-
Mining quantitative association rules in large relational tables
-
Montreal, Quebec, Canada, June
-
Srikant, R., Agrawal, R.: Mining Quantitative Association Rules in Large Relational Tables, ACM SIGMOD International Conference on Management of Data, Montreal, Quebec, Canada, June 1996.
-
(1996)
ACM SIGMOD International Conference on Management of Data
-
-
Srikant, R.1
Agrawal, R.2
-
35
-
-
35748943218
-
A discretization algorithm based on Class-Attribute Contingency Coefficient
-
Tsai, C.-J., Lee, C.-I., Yang,W.-P.: A discretization algorithm based on Class-Attribute Contingency Coefficient, Information Science, 178(3), 2008, 714-731.
-
(2008)
Information Science
, vol.178
, Issue.3
, pp. 714-731
-
-
Tsai, C.-J.1
Lee, C.-I.2
Yang, W.-P.3
-
36
-
-
51349137112
-
Risk mining for infection control
-
Communications and Discoveries from Multidisciplinary Data (S. Iwata, Y. Ohsawa, S. Tsumoto, N. Zhong, Y. Shi, L. Magnani, Eds.) Springer, Heidelberg
-
Tsumoto, S., Matsuoka, K., Yokoyama, S.: Risk Mining for Infection Control, in: Communications and Discoveries from Multidisciplinary Data (S. Iwata, Y. Ohsawa, S. Tsumoto, N. Zhong, Y. Shi, L. Magnani, Eds.), vol.123 of Studies in Computational Intelligence, Springer, Heidelberg, 2008, 283-297
-
(2008)
Studies in Computational Intelligence
, vol.123
, pp. 283-297
-
-
Tsumoto, S.1
Matsuoka, K.2
Yokoyama, S.3
-
37
-
-
84971641220
-
SIA: A supervised inductive algorithm with genetic search for learning attrib-ute based concepts
-
Proceedings of the European Conference on Machine Learning Viena, Austria, April
-
Venturini, G.: SIA: a supervised inductive algorithm with genetic search for learning attrib-ute based concepts, in: Proceedings of the European Conference on Machine Learning, vol.667 of Lecture Notes in Computer Science, Viena, Austria, April 1993, 280-296.
-
(1993)
Lecture Notes in Computer Science
, vol.667
, pp. 280-296
-
-
Venturini, G.1
-
38
-
-
0003970654
-
-
Kluwer Academic Publishers, Norwell, MA, USA
-
Wong, M. L., Leung, K. S.: Data Mining Using Grammar-Based Genetic Programming and Applications, Kluwer Academic Publishers, Norwell, MA, USA, 2000.
-
(2000)
Data Mining Using Grammar-Based Genetic Programming and Applications
-
-
Wong, M.L.1
Leung, K.S.2
-
39
-
-
23744471269
-
ARMGA: Identifying interesting association rules with genetic algorithms
-
Yan, X., Zhang, C., Zhang, S.: ARMGA: Identifying Interesting Association Rules with Genetic Algorithms, Applied Artificial Intelligence, 19(7), 2005, 677-689.
-
(2005)
Applied Artificial Intelligence
, vol.19
, Issue.7
, pp. 677-689
-
-
Yan, X.1
Zhang, C.2
Zhang, S.3
-
40
-
-
56349170668
-
Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support
-
Yan, X., Zhang, C., Zhang, S.: Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support, Expert Systems with Applications, 36(2), 2009, 3066-3076.
-
(2009)
Expert Systems with Applications
, vol.36
, Issue.2
, pp. 3066-3076
-
-
Yan, X.1
Zhang, C.2
Zhang, S.3
-
42
-
-
0042823817
-
Association rule mining: Models and algorithms series
-
Springer-Verlag, Berlin
-
Zhang, C., Zhang, S.: Association Rule Mining: Models and Algorithms Series, Lecture Notes in Computer Science, LNAI 2307, Springer-Verlag, Berlin, 2002.
-
(2002)
Lecture Notes in Computer Science, LNAI
, vol.2307
-
-
Zhang, C.1
Zhang, S.2
|