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Advances in Intelligent Data Analysis. Reasoning about Data

Second International Symposium, IDA-97, London, UK, August 4-6, 1997, Proceedings

  • Conference proceedings
  • © 1997

Overview

Editors:
  1. Xiaohui Liu
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  2. Paul Cohen
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  3. Michael Berthold
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1280)

Included in the following conference series:

Conference proceedings info: IDA 1997.

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About this book

This book constitutes the refereed proceedings of the Second International Symposium on Intelligent Data Analysis, IDA-97, held in London, UK, in August 1997.
The volume presents 50 revised full papers selected from a total of 107 submissions. Also included is a keynote, Intelligent Data Analysis: Issues and Opportunities, by David J. Hand. The papers are organized in sections on exploratory data analysis, preprocessing and tools; classification and feature selection; medical applications; soft computing; knowledge discovery and data mining; estimation and clustering; data quality; qualitative models.

Keywords

Table of contents (51 papers)

  1. Front Matter

    Pages I-XII
    Download chapter PDF

  2. Intelligent data analysis: Issues and opportunities

    • David J. Hand
    Pages 1-14

  3. Decomposition of heterogeneous classification problems

    • Chidanand Apte, Se June Hong, Jonathan R. M. Hosking, Jorge Lepre, Edwin P. D. Pednault, Barry K. Rosen
    Pages 17-28

  4. Managing dialogue in a statistical expert assistant with a cluster-based user model

    • Michael William Muller
    Pages 29-40

  5. How to find big-oh in your data set (and how not to)

    • C. C. McGeoch, D. Precup, P. R. Cohen
    Pages 41-52

  6. Data classification using a W.I.S.E. toolbox

    • Ian Berry, Paul Gough
    Pages 53-64

  7. Mill's methods for complete Intelligent Data Analysis

    • Tremaine A. O. Cornish
    Pages 65-76

  8. Integrating many techniques for discovering structure in data

    • Dawn E. Gregory, Paul R. Cohen
    Pages 77-88

  9. Meta-Reasoning for Data Analysis Tool Allocation

    • Robert Levinson, Jeff Wilkinson
    Pages 89-100

  10. Navigation for data analysis systems

    • Robert St. Amant
    Pages 101-109

  11. An annotated data collection system to support intelligent analysis of Intensive Care Unit data

    • Christine L. Tsien, James C. Fackler
    Pages 111-121

  12. A combined approach to uncertain data analysis

    • Hairong Yu, Arthur Ramer
    Pages 123-134

  13. A connectionist approach to the distance-based analysis of relational data

    • Kristina Schädler, Fritz Wysotzki
    Pages 137-148

  14. Efficient GA based techniques for automating the design of classification models

    • Robin Glover, Peter Sharpe
    Pages 149-160

  15. Data representations and machine learning techniques

    • C. P. Lam, G. A. W. West, T. M. Caelli
    Pages 161-172

  16. Development of a knowledge-driven constructive induction mechanism

    • Suzanne Lo, A. Famili
    Pages 173-185

  17. Oblique linear tree

    • João Gama
    Pages 187-198

  18. Feature selection for neural networks through functional links found by evolutionary computation

    • S. Haring, J. N. Kok, M. C. van Wezel
    Pages 199-210

  19. Building simple models: A case study with decision trees

    • David Jensen, Tim Oates, Paul R. Cohen
    Pages 211-222

  20. Exploiting symbolic learning in visual inspection

    • M. Piccardi, R. Cucchiara, M. Bariani, P. Mello
    Pages 223-234
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