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  • Textbook
  • © 2001

Machine Learning and Its Applications

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Editors:

  1. Georgios Paliouras

    1. National Centre for Scientific Research “Demokritos”, Institute of Informatics and Telecommunications, Athens, Greece

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  2. Vangelis Karkaletsis

    1. National Centre for Scientific Research “Demokritos”, Institute of Informatics and Telecommunications, Athens, Greece

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    You can also search for this editor in PubMed   Google Scholar

  3. Constantine D. Spyropoulos

    1. National Centre for Scientific Research “Demokritos”, Institute of Informatics and Telecommunications, Athens, Greece

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2049)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (21 chapters)

  1. Front Matter

    Pages I-VIII
    PDF

  2. Methods

    2. Learning Patterns in Noisy Data: The AQ Approach

      • Ryszard S. Michalski, Kenneth A. Kaufman
      Pages 22-38

    4. Function Decomposition in Machine Learning

      • Blaž Zupan, Ivan Bratko, Marko Bohanec, Janez Demšar
      Pages 71-101

    6. Case-Based Reasoning

      • Ramon Lopez de Mantaras
      Pages 127-145

    7. Genetic Algorithms in Machine Learning

      • Jonathan Shapiro
      Pages 146-168

    8. Pattern Recognition and Neural Networks

      • Sergios Theodoridis, Konstantinos Koutroumbas
      Pages 169-195

    10. Integrated Architectures for Machine Learning

      • Lorenza Saitta
      Pages 218-229

    12. Support Vector Machines: Theory and Applications

      • Theodoros Evgeniou, Massimiliano Pontil
      Pages 249-257

    14. Machine Learning in Human Language Technology

      • Nikos D. Fakotakis, Kyriakos N. Sgarbas
      Pages 267-273

    15. Machine Learning for Intelligent Information Access

      • Grigoris Karakoulas, Giovanni Semeraro
      Pages 274-280

    16. Machine Learning and Intelligent Agents

      • Themis Panayiotopoulos, Nick Z. Zacharis
      Pages 281-285

    17. Machine Learning in User Modeling

      • Christos Papatheodorou
      Pages 286-294

    18. Data Mining in Economics, Finance, and Marketing

      • Hans C. Jessen, Georgios Paliouras
      Pages 295-299

    19. Machine Learning in Medical Applications

      • George D. Magoulas, Andriana Prentza
      Pages 300-307
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About this book

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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Keywords

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Editors and Affiliations

  • National Centre for Scientific Research “Demokritos”, Institute of Informatics and Telecommunications, Athens, Greece

    Georgios Paliouras, Vangelis Karkaletsis, Constantine D. Spyropoulos

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Bibliographic Information

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Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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