-
2
-
-
1842704721
-
An iterative Bayesian algorithm for categorization
-
Fisher, D., Pazzani, M., & Langley, P. (Eds.), San Mateo, CA: Morgan Kaufmann
-
Anderson, J. R., & Matessa, M. (1991). An iterative Bayesian algorithm for categorization. In Fisher, D., Pazzani, M., & Langley, P. (Eds.), Concept formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann.
-
(1991)
Concept Formation: Knowledge and Experience in Unsupervised Learning
-
-
Anderson, J.R.1
Matessa, M.2
-
3
-
-
0002294427
-
ITERATE: A conceptual clustering method for knowledge discovery in databases
-
Braunschweig, B., & Day, R. (Eds.), Editions Technip
-
Biswas, G., Weinberg, J., & Li, C. (1994). ITERATE: A conceptual clustering method for knowledge discovery in databases. In Braunschweig, B., & Day, R. (Eds.), Innovative Applications of Artificial Intelligence in the Oil and Gas Industry. Editions Technip.
-
(1994)
Innovative Applications of Artificial Intelligence in the Oil and Gas Industry
-
-
Biswas, G.1
Weinberg, J.2
Li, C.3
-
4
-
-
0011909134
-
Conceptual clustering and exploratory data analysis
-
San Mateo, CA: Morgan Kaufmann
-
Biswas, G., Weinberg, J. B., Yang, Q., & Koller, G. R. (1991). Conceptual clustering and exploratory data analysis. In Proceedings of the Eighth International Machine Learning Workshop, pp. 591-595. San Mateo, CA: Morgan Kaufmann.
-
(1991)
Proceedings of the Eighth International Machine Learning Workshop
, pp. 591-595
-
-
Biswas, G.1
Weinberg, J.B.2
Yang, Q.3
Koller, G.R.4
-
6
-
-
84943175777
-
AUTOCLASS: A Bayesian classification system
-
Ann Arbor, MI: Morgan Kaufmann
-
Cheeseman, P., Kelly, J., Self, M., Stutz, J., Taylor, W., & Freeman, D. (1988). AUTOCLASS: A Bayesian classification system. In Proceedings of the Fifth International Machine Learning Conference, pp. 54-64. Ann Arbor, MI: Morgan Kaufmann.
-
(1988)
Proceedings of the Fifth International Machine Learning Conference
, pp. 54-64
-
-
Cheeseman, P.1
Kelly, J.2
Self, M.3
Stutz, J.4
Taylor, W.5
Freeman, D.6
-
7
-
-
0000353884
-
Explaining basic categories: Feature predictability and information
-
Corter, J., & Gluck, M. (1992). Explaining basic categories: feature predictability and information. Psychological Bulletin, 111, 291-303.
-
(1992)
Psychological Bulletin
, vol.111
, pp. 291-303
-
-
Corter, J.1
Gluck, M.2
-
9
-
-
8644281839
-
Description contrasting in incremental concept formation
-
Kodratoff, Y. (Ed.), Springer-Verlag
-
Decaestecker, C. (1991). Description contrasting in incremental concept formation. In Kodratoff, Y. (Ed.), Machine Learning - EWSL-91, No. 482, Lecture Notes in Artificial Intelligence, pp. 220-233. Springer-Verlag.
-
(1991)
Machine Learning - EWSL-91, No. 482, Lecture Notes in Artificial Intelligence
, vol.482
, pp. 220-233
-
-
Decaestecker, C.1
-
10
-
-
8644267372
-
-
Personal communication, oct. 1993
-
Devaney, M., & Ram, A. (1993). Personal communication, oct. 1993.
-
(1993)
-
-
Devaney, M.1
Ram, A.2
-
13
-
-
0003586436
-
-
Ph.D. thesis, University of Michigan, Ann Arbor, MI: Department of Computer Science and Engineering
-
Fayyad, U. (1991). On the Induction of Decision Trees for Multiple Concept Learning. Ph.D. thesis, University of Michigan, Ann Arbor, MI: Department of Computer Science and Engineering.
-
(1991)
On the Induction of Decision Trees for Multiple Concept Learning
-
-
Fayyad, U.1
-
16
-
-
84946966738
-
Applying AI clustering to engineering tasks
-
Fisher, D., Xu, L., Carnes, J., Reich, Y., Fenves, S., Chen, J., Shiavi, R., Biswas, G., & Weinberg, J. (1993). Applying AI clustering to engineering tasks. IEEE Expert, 8, 51-60.
-
(1993)
IEEE Expert
, vol.8
, pp. 51-60
-
-
Fisher, D.1
Xu, L.2
Carnes, J.3
Reich, Y.4
Fenves, S.5
Chen, J.6
Shiavi, R.7
Biswas, G.8
Weinberg, J.9
-
17
-
-
85152529520
-
Ordering effects in clustering
-
San Mateo, CA: Morgan Kaufmann
-
Fisher, D., Xu, L., & Zard, N. (1992). Ordering effects in clustering. In Proceedings of the Ninth International Conference on Machine Learning, pp. 163-168. San Mateo, CA: Morgan Kaufmann.
-
(1992)
Proceedings of the Ninth International Conference on Machine Learning
, pp. 163-168
-
-
Fisher, D.1
Xu, L.2
Zard, N.3
-
18
-
-
0343442766
-
Knowledge acquisition via incremental conceptual clustering
-
Fisher, D. H. (1987a). Knowledge acquisition via incremental conceptual clustering. Machine Learning, 2, 139-172.
-
(1987)
Machine Learning
, vol.2
, pp. 139-172
-
-
Fisher, D.H.1
-
19
-
-
0011840676
-
-
Ph.D. thesis, University of California, Irvine, CA: Department of Information and Computer Science
-
Fisher, D. H. (1987b). Knowledge Acquisition via Incremental Conceptual Clustering. Ph.D. thesis, University of California, Irvine, CA: Department of Information and Computer Science.
-
(1987)
Knowledge Acquisition Via Incremental Conceptual Clustering
-
-
Fisher, D.H.1
-
21
-
-
77957077963
-
The structure and formation of natural categories
-
Bower, G. H. (Ed.), San Diego, CA: Academic Press
-
Fisher, D. H., & Langley, P. (1990). The structure and formation of natural categories. In Bower, G. H. (Ed.), The Psychology of Learning and Motivation, Vol. 25. San Diego, CA: Academic Press.
-
(1990)
The Psychology of Learning and Motivation
, vol.25
-
-
Fisher, D.H.1
Langley, P.2
-
24
-
-
0024732990
-
Models of incremental concept formation
-
Gennari, J., Langley, P., & Fisher, D. (1989). Models of incremental concept formation. Artificial Intelligence, 40, 11-62.
-
(1989)
Artificial Intelligence
, vol.40
, pp. 11-62
-
-
Gennari, J.1
Langley, P.2
Fisher, D.3
-
25
-
-
0002410338
-
Information, uncertainty, and the utility of categories
-
Hillsdale, NJ: Lawrence Erlbaum
-
Gluck, M. A., & Corter, J. E. (1985). Information, uncertainty, and the utility of categories. In Proceedings of the Seventh Annual Conference of the Cognitive Science Society, pp. 283-287. Hillsdale, NJ: Lawrence Erlbaum.
-
(1985)
Proceedings of the Seventh Annual Conference of the Cognitive Science Society
, pp. 283-287
-
-
Gluck, M.A.1
Corter, J.E.2
-
27
-
-
0002463937
-
Bayesian classification with correlation and inheritance
-
San Mateo, CA: Morgan Kaufmann
-
Hanson, R., Stutz, J., & Cheeseman, P. (1991). Bayesian classification with correlation and inheritance. In Proceedings of the 12th International Joint Conference on Artificial Intelligence, pp. 692-698. San Mateo, CA: Morgan Kaufmann.
-
(1991)
Proceedings of the 12th International Joint Conference on Artificial Intelligence
, pp. 692-698
-
-
Hanson, R.1
Stutz, J.2
Cheeseman, P.3
-
28
-
-
0000148778
-
A heuristic approach to the discovery of macro operators
-
Iba, G. (1989). A heuristic approach to the discovery of macro operators. Machine Learning, 3, 285-317.
-
(1989)
Machine Learning
, vol.3
, pp. 285-317
-
-
Iba, G.1
-
29
-
-
2442601736
-
Learning to recognize movements
-
Fisher, D., Pazzani, M., & Langley, P. (Eds.), San Mateo, CA: Morgan Kaufmann
-
Iba, W., & Gennari, J. (1991). Learning to recognize movements. In Fisher, D., Pazzani, M., & Langley, P. (Eds.), Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann.
-
(1991)
Concept Formation: Knowledge and Experience in Unsupervised Learning
-
-
Iba, W.1
Gennari, J.2
-
30
-
-
84949873054
-
Hierarchical clustering of composite objects with a variable number of components
-
Ketterlin, A., Gancarski, P., & Korczak, J. (1995). Hierarchical clustering of composite objects with a variable number of components. In Preliminary papers of the Fifth International Workshop on Artificial Intelligence and Statistics, pp. 303-309.
-
(1995)
Preliminary Papers of the Fifth International Workshop on Artificial Intelligence and Statistics
, pp. 303-309
-
-
Ketterlin, A.1
Gancarski, P.2
Korczak, J.3
-
31
-
-
8644242893
-
-
Ph.D. thesis, Stockholm University, Stockholm, Sweden: Department of Computer and Systems Sciences
-
Kilander, F. (1994). Incremental Conceptual Clustering in an On-Line Application. Ph.D. thesis, Stockholm University, Stockholm, Sweden: Department of Computer and Systems Sciences.
-
(1994)
Incremental Conceptual Clustering in An On-Line Application
-
-
Kilander, F.1
-
32
-
-
24144502661
-
Reconstructive memory: A computer model
-
Kolodner, J. L. (1983). Reconstructive memory: A computer model. Cognitive Science, 7, 281-328.
-
(1983)
Cognitive Science
, vol.7
, pp. 281-328
-
-
Kolodner, J.L.1
-
33
-
-
8644231567
-
Correcting erroneous generalizations
-
Lebowitz, M. (1982). Correcting erroneous generalizations. Cognition and Brain Theory, 5, 367-381.
-
(1982)
Cognition and Brain Theory
, vol.5
, pp. 367-381
-
-
Lebowitz, M.1
-
34
-
-
0000166613
-
Experiments with incremental concept formation: UNIMEM
-
Lebowitz, M. (1987). Experiments with incremental concept formation: UNIMEM. Machine Learning, 2, 103-138.
-
(1987)
Machine Learning
, vol.2
, pp. 103-138
-
-
Lebowitz, M.1
-
36
-
-
0025798330
-
A distance-based attribute selection measure for decision tree induction
-
Lopez de Mantaras, R. (1991). A distance-based attribute selection measure for decision tree induction. Machine Learning, 6, 81-92.
-
(1991)
Machine Learning
, vol.6
, pp. 81-92
-
-
Lopez De Mantaras, R.1
-
37
-
-
2342463258
-
Acquiring and combining overlapping concepts
-
Martin, J., & Billman, D. (1994). Acquiring and combining overlapping concepts. Machine Learning, 16, 121-155.
-
(1994)
Machine Learning
, vol.16
, pp. 121-155
-
-
Martin, J.1
Billman, D.2
-
40
-
-
85131465852
-
Structural principles of categorization
-
Tighe, T., & Shepp, B. (Eds.), Hillsdale, NJ: Lawrence Erlbaum
-
Medin, D. (1983). Structural principles of categorization. In Tighe, T., & Shepp, B. (Eds.), Perception, Cognition, and Development, pp. 203-230. Hillsdale, NJ: Lawrence Erlbaum.
-
(1983)
Perception, Cognition, and Development
, pp. 203-230
-
-
Medin, D.1
-
42
-
-
0003046842
-
Learning from observation: Conceptual clustering
-
Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (Eds.), San Mateo, CA: Morgan Kaufmann
-
Michalski, R. S., & Stepp, R. (1983b). Learning from observation: conceptual clustering. In Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (Eds.), Machine Learning: An Artificial Intelligence Approach. San Mateo, CA: Morgan Kaufmann.
-
(1983)
Machine Learning: An Artificial Intelligence Approach
-
-
Michalski, R.S.1
Stepp, R.2
-
43
-
-
79952785777
-
An empirical comparison of pruning methods for decision-tree induction
-
Mingers, J. (1989a). An empirical comparison of pruning methods for decision-tree induction. Machine Learning, 4, 227-243.
-
(1989)
Machine Learning
, vol.4
, pp. 227-243
-
-
Mingers, J.1
-
44
-
-
34249966833
-
An empirical comparison of selection measures for decision-tree induction
-
Mingers, J. (1989b). An empirical comparison of selection measures for decision-tree induction. Machine Learning, 3, 319-342.
-
(1989)
Machine Learning
, vol.3
, pp. 319-342
-
-
Mingers, J.1
-
45
-
-
0029185047
-
A branch and bound incremental conceptual clusterer
-
Nevins, A. J. (1995). A branch and bound incremental conceptual clusterer. Machine Learning, 18, 5-22.
-
(1995)
Machine Learning
, vol.18
, pp. 5-22
-
-
Nevins, A.J.1
-
46
-
-
33744584654
-
Induction of decision trees
-
Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1, 81-106.
-
(1986)
Machine Learning
, vol.1
, pp. 81-106
-
-
Quinlan, J.R.1
-
49
-
-
0002908586
-
The formation and use of abstract concepts in design
-
Fisher, D., Pazzani, M., & Langley, P. (Eds.), San Mateo, CA: Morgan Kaufmann
-
Reich, Y., & Fenves, S. (1991). The formation and use of abstract concepts in design. In Fisher, D., Pazzani, M., & Langley, P. (Eds.), Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann.
-
(1991)
Concept Formation: Knowledge and Experience in Unsupervised Learning
-
-
Reich, Y.1
Fenves, S.2
-
50
-
-
85152519885
-
An improved algorithm for incremental induction of decision trees
-
San Mateo, CA: Morgan Kaufmann
-
Utgoff, P. (1994). An improved algorithm for incremental induction of decision trees. In Proceedings of the Eleventh International Conference on Machine Learning, pp. 318-325. San Mateo, CA: Morgan Kaufmann.
-
(1994)
Proceedings of the Eleventh International Conference on Machine Learning
, pp. 318-325
-
-
Utgoff, P.1
-
51
-
-
0008137501
-
Intrinsic classification by MML - The SNOB program
-
UNE, Armidale, NSW, Australia: World Scientific
-
Wallace, C. S., & Dowe, D. L. (1994). Intrinsic classification by MML - the SNOB program. In Proceedings of the 7th Australian Joint Conference on Artificial Intelligence, pp. 37-44. UNE, Armidale, NSW, Australia: World Scientific.
-
(1994)
Proceedings of the 7th Australian Joint Conference on Artificial Intelligence
, pp. 37-44
-
-
Wallace, C.S.1
Dowe, D.L.2
-
53
-
-
8644270336
-
A self-organized knowledge base for recall, design, and discovery in organic chemistry
-
Pierce, T. H., & Hohne, B. A. (Eds.), Washington, DC: American Chemical Society
-
Wilcox, C. S., & Levinson, R. A. (1986). A self-organized knowledge base for recall, design, and discovery in organic chemistry. In Pierce, T. H., & Hohne, B. A. (Eds.), Artificial Intelligence Applications in Chemistry. Washington, DC: American Chemical Society.
-
(1986)
Artificial Intelligence Applications in Chemistry
-
-
Wilcox, C.S.1
Levinson, R.A.2
|