-
1
-
-
0002431740
-
Automatic construction of decision trees from data: A multidisciplinary survey
-
Murthy S., K (1998). Automatic construction of decision trees from data: A multidisciplinary survey. Data Mining and Knowledge Discovery.
-
(1998)
Data Mining and Knowledge Discovery
-
-
Murthy, S.K.1
-
2
-
-
33744584654
-
Induction of decision trees
-
1986
-
Quinlan, R. (1986). Induction of decision trees, Machine Learning, 1:81-106,1986
-
(1986)
Machine Learning
, vol.1
, pp. 81-106
-
-
Quinlan, R.1
-
3
-
-
0003802343
-
-
Wadsworh International Group
-
Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J. (1984) Classification and Regression Trees. Wadsworh International Group.
-
(1984)
Classification and Regression Trees
-
-
Breiman, L.1
Friedman, J.H.2
Olshen, R.A.3
Stone, C.J.4
-
6
-
-
0003586436
-
-
Doctoral dissertation, Department of Electrical Engineering and Computer Science, Univercity of Michigan
-
Fayyad, M.U. (1991). On the Induction of Decision Trees for Multiple Concept Learning, Doctoral dissertation, Department of Electrical Engineering and Computer Science, Univercity of Michigan.
-
(1991)
On the Induction of Decision Trees for Multiple Concept Learning
-
-
Fayyad, M.U.1
-
9
-
-
0024735689
-
Classifier Systems and Genetic Algorithms
-
Booker L.B., D.E. Goldberg & J.H. Holland (1989). Classifier Systems and Genetic Algorithms, Artificial Intelligence, 40, 2, 235-282.
-
(1989)
Artificial Intelligence
, vol.40
, Issue.2
, pp. 235-282
-
-
Booker, L.B.1
Goldberg, D.E.2
Holland, J.H.3
-
10
-
-
0027696338
-
Using genetic algorithms for concept learning
-
DeJong, K.A., Spears, W. M., & Gordon, D.F. (1993). Using genetic algorithms for concept learning. Machine Learning, 13, 161-188.
-
(1993)
Machine Learning
, vol.13
, pp. 161-188
-
-
DeJong, K.A.1
Spears, W.M.2
Gordon, D.F.3
-
11
-
-
0027696178
-
A knowledge-intensive genetic algorithm for supervised learning
-
Janikow, C., Z. (1993) A knowledge-intensive genetic algorithm for supervised learning, Machine Learning, 13,189-228.
-
(1993)
Machine Learning
, vol.13
, pp. 189-228
-
-
Janikow, C.Z.1
-
14
-
-
0003065528
-
Further Research on Feature Selection and Classification Using Genetic Algorithms
-
Punch, W.F., Goodman E.D., Pei Min, Chia-Shun Lai, Hovland P. & Enbody R. (1993). Further Research on Feature Selection and Classification Using Genetic Algorithms. Proceedings of ICGA93, 557-564.
-
(1993)
Proceedings of ICGA93
, pp. 557-564
-
-
Punch, W.F.1
Goodman, E.D.2
Min, P.3
Lai, C.-S.4
Hovland, P.5
Enbody, R.6
-
15
-
-
0000865580
-
Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm
-
Turney, D.P (1995). Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm. Journal of Artificial Intelligence Research, 2, 369-409.
-
(1995)
Journal of Artificial Intelligence Research
, vol.2
, pp. 369-409
-
-
Turney, D.P.1
-
16
-
-
85027109147
-
-
IEEE Computer Society Press, Los Alamos, CA
-
Vafaie, H., DeJong, K. (1992). Genetic Algorithms as a Tool for Feature Selection in Machine Learning. IEEE Computer Society Press, Los Alamos, CA, 200-203.
-
(1992)
Genetic Algorithms As A Tool for Feature Selection in Machine Learning
, pp. 200-203
-
-
Vafaie, H.1
DeJong, K.2
-
17
-
-
0002640910
-
Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification
-
Bala, J., Huang, J., Vafaie, H., DeJong, K., Wechsler, H. (1995). Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification. Proceedings of IJCAI95, Montreal.
-
(1995)
Proceedings of IJCAI95, Montreal
-
-
Bala, J.1
Huang, J.2
Vafaie, H.3
DeJong, K.4
Wechsler, H.5
-
18
-
-
0001259758
-
Overfitting avoidance as bias
-
Schaffer, C. (1993). Overfitting avoidance as bias, Machine Learning, 10, 153-178
-
(1993)
Machine Learning
, vol.10
, pp. 153-178
-
-
Schaffer, C.1
-
19
-
-
0016331864
-
Performance bounds on the splitting algorithm for binary testing
-
Fasc. 4
-
Garey R., M, and Graham L.,R (1974) Performance bounds on the splitting algorithm for binary testing. Acta Informatica, 3(Fasc. 4):347-355.
-
(1974)
Acta Informatica
, vol.3
, pp. 347-355
-
-
Garey, R.M.1
Graham, L.R.2
-
21
-
-
0002591462
-
Lookahead Feature Construction for Learning Hard Concepts
-
Amherst, MA, (Morgan Kaufmann, San Francisco, CA)
-
Ragavan, H. and L. Rendell (1993), Lookahead Feature Construction for Learning Hard Concepts, Proceedings of the Tenth International Conference on Machine Learning, Amherst, MA, pp. 252-259 (Morgan Kaufmann, San Francisco, CA).
-
(1993)
Proceedings of the Tenth International Conference on Machine Learning
, pp. 252-259
-
-
Ragavan, H.1
Rendell, L.2
-
28
-
-
0027580356
-
Very simple classification rules perform well on most commonly used datasets
-
Holte, R.C. (1993). Very simple classification rules perform well on most commonly used datasets, Machine Learning 11,63-91.
-
(1993)
Machine Learning
, vol.11
, pp. 63-91
-
-
Holte, R.C.1
-
29
-
-
84863387880
-
-
Irvine, CA: Department of Information and Computer Science
-
Blake, C., Keogh, E., & Merz, J. (2000) UCI Repository of machine learning databases [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.
-
(2000)
UCI Repository of Machine Learning Databases
-
-
Blake, C.1
Keogh, E.2
Merz, J.3
|