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  • © 2010

Advances in Machine Learning and Data Analysis

  • Offers the state of the art of tremendous advances in machine learning and data analysis
  • Serves as an excellent reference text for researchers and graduate students, working on machine learning and data analysis
  • Contains sixteen revised and extended research articles written by prominent researchers

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 48)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-viii
  2. 2D/3D Image Data Analysis for Object Tracking and Classification

    • Seyed Eghbal Ghobadi, Omar Edmond Loepprich, Oliver Lottner, Klaus Hartmann, Wolfgang Weihs, Otmar Loffeld
    Pages 1-13
  3. Robot Competence Development by Constructive Learning

    • Q. Meng, M. H. Lee, C. J. Hinde
    Pages 15-26
  4. An Asymptotic Method to a Financial Optimization Problem

    • Dejun Xie, David Edwards, Giberto Schleiniger
    Pages 79-94
  5. Improving Low-Cost Sail Simulator Results by Artificial Neural Networks Models

    • V. Díaz Casás, P. Porca Belío, F. López Peña, R. J. Duro
    Pages 139-149
  6. A New Robust Combined Method for Auto Exposure and Auto White-Balance

    • Quoc Kien Vuong, Se-Hwan Yun, Suki Kim
    Pages 165-178
  7. Harmonic Analysis and Optimum Allocation of Filters in CSCT

    • Mohammad Golkhah, Mohammad Tavakoli Bina
    Pages 191-202
  8. Digital Pen and Paper Technology as a Means of Classroom Administration Relief

    • Jan Broer, Tim Wendisch, Nina Willms
    Pages 203-215
  9. A Conceptual Model for a Network-Based Assessment Security System

    • Nathan Percival, Jennifer Percival, Clemens Martin
    Pages 217-230
  10. Incorrect Weighting of Absolute Performance in Self-Assessment

    • Scott A. Jeffrey, Brian Cozzarin
    Pages 231-239

About this book

A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2008). This volume contains sixteen revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Advances in Machine Learning and Data Analysis offers the state of the art of tremendous advances in machine learning and data analysis and also serves as an excellent reference text for researchers and graduate students, working on machine learning and data analysis.

Reviews

From the reviews: “This is a collection of papers from a large international conference on advances in machine learning and data analysis … . Readers who work with digital systems … would benefit most from this book. … Each chapter has … a bibliography that helps readers find further references, when needed. … the topics covered in this book should be of great interest to researchers and practitioners who want to apply machine learning technology and data analysis tools to problems in general electrical engineering areas … .” (Xiannong Meng, ACM Computing Reviews, March, 2010)

Editors and Affiliations

  • Dept. Chemical Engineering, California State University, Long Beach, USA

    Mahyar A. Amouzegar

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access