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Machine Learning of Inductive Bias (The Springer International Series in Engineering and Computer Science)

Paul E. Utgoff

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ISBN 10: 0898382238 / ISBN 13: 9780898382235
Published by Springer, 1986
New Condition: New Hardcover
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Bibliographic Details

Title: Machine Learning of Inductive Bias (The ...

Publisher: Springer

Publication Date: 1986

Binding: Hardcover

Book Condition:New

Edition: 1986.

About this title

Synopsis:

This book is based on the author's Ph.D. dissertation[56]. The the­ sis research was conducted while the author was a graduate student in the Department of Computer Science at Rutgers University. The book was pre­ pared at the University of Massachusetts at Amherst where the author is currently an Assistant Professor in the Department of Computer and Infor­ mation Science. Programs that learn concepts from examples are guided not only by the examples (and counterexamples) that they observe, but also by bias that determines which concept is to be considered as following best from the ob­ servations. Selection of a concept represents an inductive leap because the concept then indicates the classification of instances that have not yet been observed by the learning program. Learning programs that make undesir­ able inductive leaps do so due to undesirable bias. The research problem addressed here is to show how a learning program can learn a desirable inductive bias.

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