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ORCIDMachine Learning, Volume 11
Volume 11, 1993
- Chris S. Wallace, Jon D. Patrick:
Coding Decision Trees. 7-22 - Sanjeev R. Kulkarni, Sanjoy K. Mitter, John N. Tsitsiklis:
Active Learning Using Arbitrary Binary Valued Queries. 23-35 - Yasubumi Sakakibara:
Noise-Tolerant Occam Algorithms and Their Applications to Learning Decision Trees. 37-62 - Robert C. Holte:
Very Simple Classification Rules Perform Well on Most Commonly Used Datasets. 63-91 - Jan L. Talmon, Herco Fonteijn, Peter J. Braspenning:
An Analysis of the WITT Algorithm. 91-104 - Ryszard S. Michalski:
Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning. 111-151 - Lorenza Saitta, Marco Botta, Filippo Neri
:
Multistrategy Learning and Theory Revision. 153-172 - Michael J. Pazzani:
Learning Causal Patterns: Making a Transition from Data-Driven to Theory-Driven Learning. 173-194 - Richard Maclin, Jude W. Shavlik:
Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. 195-215 - Katharina Morik:
Balanced Cooperative Modeling. 217-235 - Gheorghe Tecuci:
Plausible Justification Trees: A Framework for Deep and Dynamic Integration of Learning Strategies. 237-261
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