Machine Learning of Inductive Bias: 15 (The Springer International Series in Engineering and Computer Science) - Softcover

Utgoff, Paul E. E.

 
9781461294085: Machine Learning of Inductive Bias: 15 (The Springer International Series in Engineering and Computer Science)
Softcover
ISBN 10: 1461294088 ISBN 13: 9781461294085
Verlag: Springer, 2012

Inhaltsangabe

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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Reseña del editor

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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2012
Sprache
Englisch
ISBN 10 
1461294088
ISBN 13 
9781461294085
Einband
Tapa blanda
Anzahl der Seiten
188
Kontakt zum Hersteller
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Weitere beliebte Ausgaben desselben Titels

9780898382235: Machine Learning of Inductive Bias: 15 (The Springer International Series in Engineering and Computer Science)

Vorgestellte Ausgabe

ISBN 10:  0898382238 ISBN 13:  9780898382235
Verlag: Springer, 1986
Hardcover