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Machine Learning, Volume 4
Volume 4, 1989
- Jaime G. Carbonell:

Editorial. Mach. Learn. 4: 5-6 (1989) - David Haussler:

Learning Conjunctive Concepts in Structural Domains. 7-40 - Raymond A. Board, Leonard Pitt:

Semi-Supervised Learning. 41-65 - B. K. Natarajan:

On Learning Sets and Functions. 67-97 - Kurt VanLehn:

Efficient Specialization of Relational Concepts. 99-106 - Thomas G. Dietterich:

News and Notes. Mach. Learn. 4: 107-109 (1989) - Jaime G. Carbonell:

Editorial. 113-115 - Paul O'Rorke:

LT Revisited: Explanation-Based Learning and the Logic of Principia Mathematica. 117-159 - Paul E. Utgoff:

Incremental Induction of Decision Trees. 161-186 - Nicholas S. Flann, Thomas G. Dietterich:

A Study of Explanation-Based Methods for Inductive Learning. 187-226 - John Mingers:

An Empirical Comparison of Pruning Methods for Decision Tree Induction. 227-243 - Bruce G. Buchanan:

Can Machine Learning Offer Anything to Expert Systems? 251-254 - Douglas B. Lenat:

When Will Machines Learn? 255-257 - Ray Bareiss, Bruce W. Porter, Kenneth S. Murray:

Supporting Start-to-Finish Development of Knowledge Bases. 259-283 - William J. Clancey:

The Knowledge Level Reinterpreted: Modeling How Systems Interact. 285-291 - Thomas R. Gruber:

Automated Knowledge Acquisition for Strategic Knowledge. 293-336 - John P. McDermott:

The World Would Be a Better Place if Non-Programmers Could Program. Mach. Learn. 4: 337-338 (1989) - B. Chandrasekaran:

Task-Structures, Knowledge Acquisition and Learning. 339-345 - Mark A. Musen:

Automated Support for Building and Extending Expert Models. 347-375 - John H. Boose, Brian R. Gaines:

Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art. 377-394

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