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Elements in Machine Learning (The Morgan Kaufmann Series in Machine Learning) (Paperback)

by Pat Langley (Author) "The ability to learn is one of the central features of intelligence, which makes it an important concern for both cognitive psychology and artificial intelligence..." (more)

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Product details

Paperback: 419 pages
Publisher: Morgan Kaufmann Publishers In (16 Nov 1995)
Language English
ISBN-10: 1558603018
ISBN-13: 978-1558603011
Product Dimensions: 23.7 x 18.7 x 2.8 cm
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Amazon.co.uk Sales Rank: 1,856,735 in Books (See Bestsellers in Books)

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Product Description

Product Description
Recent years have seen an explosion of work on machine learning, the computational study of algorithms that improve performance based on experience. Research on rule induction, neural networks, genetic algorithms, case-based reasoning, and probabilistic inference has produced a variety of robust methods for inducing knowledge from training data. This book covers the main induction algorithms explored in the literature and presents them within a coherent theoretical framework that moves beyond traditional paradigm boundaries. Elements of Machine Learning provides a comprehensive introduction to the fundamental concepts and problems in the field. The book illustrates a variety of basic algorithms for inducing simple concepts from experience, presents alternatives for organizing learned concepts into large-scale structures, and discusses adaptations of the learning methods to more complex problem-solving tasks. The chapters describe these computational techniques in detail and give examples of their operation, along with exercises and references to the literature. This text is suitable for use in graduate courses on machine learning. Researchers and students in artificial intelligence, cognitive science, and statistics will find it a useful and informative addition to their libraries.

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By Pat Langley

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The ability to learn is one of the central features of intelligence, which makes it an important concern for both cognitive psychology and artificial intelligence (AI). Read the first page

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