Knowledge Discovery in Databases: an Overview (1992)

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by William J. Frawley , Gregory Piatetsky-shapiro , Christopher J. Matheus
Citations:353 - 3 self

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7 Constructing New Attributes for Decision Tree Learning – Zijian Zheng - 1996
Handbook of Perception and Cognition, Vol.14 Chapter 4: Machine Learning – Stuart Russell
8 Machine Learning – Stuart Russell
14 Induction over the unexplained: Using overly-general domain theories to aid concept learning – Raymond J. Mooney - 1993
160 Incremental Induction of Decision Trees – Paul Utgoff Utgoff - 1989
1 Paradigms for Machine Learning – Jeffrey C. Schlimmer, Pat Langley - 1991
113 Theory Refinement Combining Analytical and Empirical Methods – Dirk Ourston, Raymond Mooney - 1994
5 Learning Unification-Based Natural Language Grammars – Miles Osborne, C. S. Lewis, Prince Caspian - 1994
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
Using Visualization to Support Data Mining Of Large . . . – Daniel A. Keim, Hans-Peter Kriegel - 1991
94 Systems for Knowledge Discovery in Databases – Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-shapiro - 1993
31 Combining Connectionist and Symbolic Learning to Refine Certainty-Factor Rule Bases – J. Jeffrey Mahoney, Raymond J. Mooney - 1993
18 Inductive Learning For Abductive Diagnosis – Cynthia A. Thompson, Raymond J. Mooney - 1994
24 Transferring Previously Learned Back-Propagation Neural Networks To New Learning Tasks – L. Y. Pratt - 1993
10 Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases – J. Jeffrey Mahoney - 1996
i To Elham ii Acknowledgements – Winton H. E. Davies, Winton H. E. Davies - 2001
44 An Extensible Meta-Learning Approach for Scalable and Accurate Inductive Learning – Philip Kin-Wah Chan - 1996
6 Concept Acquisition by Autonomous Agents: Cognitive Modeling versus the Engineering Approach – Paul Davidsson - 1992
6 Feature Discovery for Inductive Concept Learning – Tom Fawcett - 1993