Models of Incremental Concept Formation
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[1] R. Detrano,et al. International application of a new probability algorithm for the diagnosis of coronary artery disease. , 1989, The American journal of cardiology.
[2] James Kelly,et al. AutoClass: A Bayesian Classification System , 1993, ML.
[3] Pat Langley,et al. Trading Off Simplicity and Coverage in Incremental concept Learning , 1988, ML.
[4] Pat Langley,et al. A Hill-Climbing Approach to Machine Discovery , 1988, ML.
[5] John J. Grefenstette,et al. Multilevel Credit Assignment in a Genetic Learning System , 1987, International Conference on Genetic Algorithms.
[6] Pat Langley,et al. A general theory of discrimination learning , 1987 .
[7] Pat Langley,et al. Hill-Climbing Theories of Learning , 1987 .
[8] David Tcheng,et al. MORE ROBUST CONCEPT LEARNING USING DYNAMICALLY – VARIABLE BIAS , 1987 .
[9] John H. Holland,et al. Escaping brittleness: the possibilities of general-purpose learning algorithms applied to parallel rule-based systems , 1995 .
[10] Douglas H. Fisher,et al. A Case Study of Incremental Concept Induction , 1986, AAAI.
[11] Richard Granger,et al. Beyond Incremental Processing: Tracking Concept Drift , 1986, AAAI.
[12] Yves Kodratoff,et al. Hierarchical Conceptual Clustering , 1986 .
[13] Stephen Jose Hanson,et al. Machine Learning, Clustering and Polymorphy , 1985, UAI.
[14] Michael Lebowitz,et al. Categorizing Numeric Information for Generalization , 1985, Cogn. Sci..
[15] Douglas H. Fisher. A hierarchical conceptual clustering algorithm , 1985 .
[16] Kenneth Wasserman. Unifying representation and generalization: understanding hierarchically structured objects , 1985 .
[17] Mark A. Gluck,et al. Information, Uncertainty and the Utility of Categories , 1985 .
[18] Herbert A. Simon,et al. EPAM-like Models of Recognition and Learning , 1984, Cogn. Sci..
[19] Robert Levinson,et al. A Self-Organizing Retrieval System for Graphs , 1984, AAAI.
[20] Michael Lebowitz,et al. Concept Learning in a Rich Input Domain: Generalization-Based Memory , 1984 .
[21] Janet L. Kolodner,et al. Maintaining Organization in a Dynamic Long-Term Memory , 1983, Cogn. Sci..
[22] R. Weale. Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .
[23] H. Barlow. Vision: A computational investigation into the human representation and processing of visual information: David Marr. San Francisco: W. H. Freeman, 1982. pp. xvi + 397 , 1983 .
[24] Ryszard S. Michalski,et al. A Theory and Methodology of Inductive Learning , 1983, Artif. Intell..
[25] R. Michalski,et al. Learning from Observation: Conceptual Clustering , 1983 .
[26] Michael Lebowitz,et al. Generalization From Natural Language Text , 1983, Cogn. Sci..
[27] Tom M. Mitchell,et al. Generalization as Search , 2002 .
[28] Edward E. Smith,et al. Categories and concepts , 1984 .
[29] Michael Lebowitz,et al. Generalization and memory in an integrated understanding system , 1980 .
[30] John R. Anderson,et al. A Learning System and Its Psychological Implications , 1979, IJCAI.
[31] Robert C. Berwick,et al. Learning Structural Descriptions of Grammar Rules from Examples , 1979, IJCAI.
[32] Eleanor Rosch,et al. Principles of Categorization , 1978 .
[33] John R. Anderson,et al. Induction of Augmented Transition Networks , 1977, Cogn. Sci..
[34] Patrick Henry Winston,et al. Learning structural descriptions from examples , 1970 .
[35] Herbert A. Simon,et al. The Sciences of the Artificial , 1970 .
[36] E. A. Feigenbaum,et al. The simulation of verbal learning behavior , 1899, IRE-AIEE-ACM '61 (Western).