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Logic for Learning

Name: Logic for Learning
Brand: Springer, Berlin
SKU: 9783540420279
Price: 271.15 RON
Availability: InStock

Learning Comprehensible Theories from Structured Data

Autor: John W. Lloyd

Limbă:

Legare: Copertă tare

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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This book is concerned with the rich and fruitful interplay between the fields of computational logi...

Informații despre carte

Autor

John W. Lloyd

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2003

Pagini

257

EAN

9783540420279

ISBN

3540420274

Enbook ID

01563453

Editura

Springer, Berlin

Greutate

525

Dimensiuni

156 x 234 x 15

Descriere completă

This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. For those in computational logic, no previous knowledge of machine learning is assumed, and for those in machine learning no previous knowledge of computational logic is assumed.The logic used throughout the book is a higher-order one, since higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation.The book should be of interest to researchers in machine learning, especially those who study learning methods for structured data. Throughout, great emphasis is placed on learning comprehensible theories. The book serves as an introduction for computational logicians to machine learning, a particularly interesting and important application area of logic, and also provides a foundation for functional logic programming languages.

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Logic for Learning

Learning Comprehensible Theories from Structured Data

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