-
9
-
-
84892263752
-
Selection of high quality rules in associative classification
-
C. Zhang Y. Zhao and L. Cao, editors, Information Science Reference, Hershey, NY, USA
-
S. Chiusano and P. Garza. Selection of high quality rules in associative classification. In C. Zhang Y. Zhao and L. Cao, editors, Post-Mining of Association RUles: Techniques for Effective Knowledge Extraction. Information Science Reference, Hershey, NY, USA, 2009.
-
(2009)
Post-Mining of Association RUles: Techniques for Effective Knowledge Extraction
-
-
Chiusano, S.1
Garza, P.2
-
11
-
-
0034593048
-
Mining the stock market: Which measure is best?
-
M. Gavrilov, D. Anguelov, P. Indyk, and R. Motwani. Mining the stock market: Which measure is best? In proceedings of the 6 th ACM Int'l Conference on Knowledge Discovery and Data Mining, pages 487-496, 2000.
-
(2000)
Proceedings of the 6th ACM Int'l Conference on Knowledge Discovery and Data Mining
, pp. 487-496
-
-
Gavrilov, M.1
Anguelov, D.2
Indyk, P.3
Motwani, R.4
-
12
-
-
33749319347
-
Interestingness measures for data mining: A survey
-
L. Geng and H. J. Hamilton. Interestingness measures for data mining: A survey. ACM Comput. Surv., 38(3):9, 2006.
-
(2006)
ACM Comput. Surv.
, vol.38
, Issue.3
, pp. 9
-
-
Geng, L.1
Hamilton, H.J.2
-
13
-
-
41549140071
-
New probabilistic interest measures for association rules
-
M. Hahsler and K. Hornik. New probabilistic interest measures for association rules. Intell. Data Anal., 11(5):437-455, 2007.
-
(2007)
Intell. Data Anal.
, vol.11
, Issue.5
, pp. 437-455
-
-
Hahsler, M.1
Hornik, K.2
-
17
-
-
64749111474
-
Comparing machine learning and knowledge discovery in databases: An application to knowledge discovery in texts
-
Springer
-
Y. Kodratoff. Comparing machine learning and knowledge discovery in databases: An application to knowledge discovery in texts. In In: ECCAI summer, pages 1-21. Springer, 2000.
-
(2000)
ECCAI Summer
, pp. 1-21
-
-
Kodratoff, Y.1
-
18
-
-
85077432727
-
On biases in estimating multi-valued attributes
-
Morgan Kaufmann
-
I. Kononenko. On biases in estimating multi-valued attributes. In in Proc. 14th Int. Joint Conf Artificial Intelligence, pages 1034-1040. Morgan Kaufmann, 1995.
-
(1995)
Proc. 14th Int. Joint Conf Artificial Intelligence
, pp. 1034-1040
-
-
Kononenko, I.1
-
19
-
-
33846419833
-
Association rule interestingness: Measure and statistical validation
-
Springer
-
S. Lallich, O. Teytaud, and E. Prudhomme. Association rule interestingness: Measure and statistical validation. In Quality Measures in Data Mining, pages 251-275. Springer, 2007.
-
(2007)
Quality Measures in Data Mining
, pp. 251-275
-
-
Lallich, S.1
Teytaud, O.2
Prudhomme, E.3
-
20
-
-
33845492839
-
Improving associative classification by incorporating novel interestingness measures
-
Washington, DC, USA, IEEE Computer Society
-
Y. Lan, D. Janssens, G. Chen, and G. Wets. Improving associative classification by incorporating novel interestingness measures. In ICEBE '05: Proceedings of the IEEE International Conference on e-Business Engineering, pages 282-288, Washington, DC, USA, 2005. IEEE Computer Society.
-
(2005)
ICEBE '05: Proceedings of the IEEE International Conference on e-Business Engineering
, pp. 282-288
-
-
Lan, Y.1
Janssens, D.2
Chen, G.3
Wets, G.4
-
21
-
-
11944264452
-
-
Technical Report LUSSI-TR-2004-01-EN, LUSSI Department, GET/ENST, France
-
P. Lenca, P. Meyer, B. Vaillant, and S. Lallich. A multicriteria decision aid for interestingness measure selection. Technical Report LUSSI-TR-2004-01-EN, LUSSI Department, GET/ENST, France, 2004.
-
(2004)
A Multicriteria Decision Aid for Interestingness Measure Selection
-
-
Lenca, P.1
Meyer, P.2
Vaillant, B.3
Lallich, S.4
-
22
-
-
33846447487
-
Association rule interestingness measures: Experimental and theoretical studies
-
Springer
-
P. Lenca, B. Vaillant, P. Meyer, and S. Lallich. Association rule interestingness measures: Experimental and theoretical studies. In Quality Measures in Data Mining, pages 51-76. Springer, 2007.
-
(2007)
Quality Measures in Data Mining
, pp. 51-76
-
-
Lenca, P.1
Vaillant, B.2
Meyer, P.3
Lallich, S.4
-
23
-
-
78149313084
-
CMAR: Accurate and efficient classification based on multiple class-association rules
-
W. Li, J. Han, and J. Pei. CMAR: Accurate and efficient classification based on multiple class-association rules. In IEEE International Conference on Data Mining (ICDM'01), San Jose, California, November 29-December 2 2001.
-
IEEE International Conference on Data Mining (ICDM'01), San Jose, California, November 29-December 2 2001
-
-
Li, W.1
Han, J.2
Pei, J.3
-
24
-
-
84948104699
-
Integrating classification and association rule mining
-
B. Liu, W. Hsu, and Y. Ma. Integrating classification and association rule mining. In KDD, pages 80-86, 1998.
-
(1998)
KDD
, pp. 80-86
-
-
Liu, B.1
Hsu, W.2
Ma, Y.3
-
26
-
-
28544452631
-
A survey of interestingness measures for knowledge discovery
-
K. McGarry. A survey of interestingness measures for knowledge discovery. Knowl. Eng. Rev., 20(1):39-61, 2005.
-
(2005)
Knowl. Eng. Rev.
, vol.20
, Issue.1
, pp. 39-61
-
-
McGarry, K.1
-
28
-
-
26844458786
-
Investigation of rule interestingness in medical data mining
-
M. Ohsaki, S. Kitaguchi, H. Yokoi, and T. Yamaguchi. Investigation of rule interestingness in medical data mining. In Active Mining, pages 174-189, 2003.
-
(2003)
Active Mining
, pp. 174-189
-
-
Ohsaki, M.1
Kitaguchi, S.2
Yokoi, H.3
Yamaguchi, T.4
-
29
-
-
0002877253
-
Discovery, analysis, and presentation of strong rules
-
G. Piatetsky-Shapiro and W.J. Frawley, editors, AAAI/MIT Press, Cambridge, MA
-
G. Piatetsky-Shapiro. Discovery, analysis, and presentation of strong rules. In G. Piatetsky-Shapiro and W.J. Frawley, editors, Knowledge Discovery in Databases. AAAI/MIT Press, Cambridge, MA, 1991.
-
(1991)
Knowledge Discovery in Databases
-
-
Piatetsky-Shapiro, G.1
-
30
-
-
2442597364
-
Discovering interesting knowledge from a science and technology database with a genetic algorithm
-
W. Romão, A. Freitas, and I. Gimenes. Discovering interesting knowledge from a science and technology database with a genetic algorithm. Appl. Soft Comput., 4(2):121-137, 2004.
-
(2004)
Appl. Soft Comput.
, vol.4
, Issue.2
, pp. 121-137
-
-
Romão, W.1
Freitas, A.2
Gimenes, I.3
-
33
-
-
1242308945
-
Selecting the right objective measure for association analysis
-
P .Tan, V. Kumar, and J. Srivastava. Selecting the right objective measure for association analysis. Inf. Syst., 29(4):293-313, 2004.
-
(2004)
Inf. Syst.
, vol.29
, Issue.4
, pp. 293-313
-
-
Tan, P.1
Kumar, V.2
Srivastava, J.3
-
34
-
-
49749113225
-
Using significant positively associated and relatively class correlated rules for associative classification of imbalanced datasets
-
Los Alamitos, IEEE Computer Society Press
-
F. Verhein and S. Chawla. Using significant positively associated and relatively class correlated rules for associative classification of imbalanced datasets. In Proceedings of the Seventh IEEE International Conference on Data Mining (ICDM '07), pages 679Ucombining double acute accent-684, Los Alamitos, 2007. IEEE Computer Society Press.
-
(2007)
Proceedings of the Seventh IEEE International Conference on Data Mining (ICDM '07)
-
-
Verhein, F.1
Chawla, S.2
-
35
-
-
0034800371
-
Principal component analysis for clustering gene expression data
-
K.Y. Yeung and W.L. Ruzzo. Principal component analysis for clustering gene expression data. Bioinformatics, 17(9):763-774, 2001. (Pubitemid 32970476)
-
(2001)
Bioinformatics
, vol.17
, Issue.9
, pp. 763-774
-
-
Yeung, K.Y.1
Ruzzo, W.L.2
|