Machine Learning and Its Applications

Advanced Lectures

By: Georgios Paliouras (Editor), Vangelis Karkaletsis (Editor), Constantine D. Spyropoulos (Editor)

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Paperback | 1 August 2001

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340 Pages

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22.86 x 15.24 x 1.91

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In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers.
This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Medicine Medicine in General Mathematics Mathematical Foundation Mathematical Logic Artificial Intelligence Machine Learning Business & Management

Business Mathematics & Systems Operating Systems Databases Human-Computer Interaction

Methods
Comparing Machine Learning and Knowledge Discovery in DataBases: An Application to Knowledge Discovery in Texts	p. 1
Learning Patterns in Noisy Data: The AQ Approach	p. 22
Unsupervised Learning of Probabilistic Concept Hierarchies	p. 39
Function Decomposition in Machine Learning	p. 71
How to Upgrade Propositional Learners to First Order Logic: A Case Study	p. 102
Case-Based Reasoning	p. 127
Genetic Algorithms in Machine Learning	p. 146
Pattern Recognition and Neural Networks	p. 169
Model Class Selection and Construction: Beyond the Procrustean Approach to Machine Learning Applications	p. 196
Integrated Architectures for Machine Learning	p. 218
Applications
The Computational Support of Scientific Discovery	p. 230
Support Vector Machines: Theory and Applications	p. 249
Pre- and Post-processing in Machine Learning and Data Mining	p. 258
Machine Learning in Human Language Technology	p. 267
Machine Learning for Intelligent Information Access	p. 274
Machine Learning and Intelligent Agents	p. 281
Machine Learning in User Modeling	p. 286
Data Mining in Economics, Finance, and Marketing	p. 295
Machine Learning in Medical Applications	p. 300
Machine Learning Applications to Power Systems	p. 308
Intelligent Techniques for Spatio-Temporal Data Analysis in Environmental Applications	p. 318
Author Index	p. 325
Table of Contents provided by Publisher. All Rights Reserved.

Machine Learning and Its Applications

Advanced Lectures

At a Glance

Paperback

Shipping

How to return your order

Defective items

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