Machine Learning of Inductive Bias

Name: Machine Learning of Inductive Bias
Brand: Springer, Berlin
SKU: 9781461294085
Price: 581.95 RON
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Autor: Paul E. Utgoff

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Editura: Springer, Berlin

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This book is based on the author's Ph.D. dissertation. The the sis research was conducted while the...

Informații despre carte

Autor

Paul E. Utgoff

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2012

Pagini

166

EAN

9781461294085

ISBN

1461294088

Enbook ID

02180048

Editura

Springer, Berlin

Greutate

296

Dimensiuni

155 x 235 x 10

Descriere completă

This book is based on the author's Ph.D. dissertation. 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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Machine Learning of Inductive Bias

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