Intelligent Information Systems 2002

Proceedings of the IIS’ 2002 Symposium, Sopot, Poland, June 3–6, 2002

ISBN: 978-3-7908-1509-2 (Print) 978-3-7908-1777-5 (Online)

Table of contents (49 chapters)

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  1. Front Matter

    Pages I-X

  2. Decision Trees and Other Classifier Systems

    1. Front Matter

      Pages 1-1

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      Pages 3-12

      A Comparison of Six Discretization Algorithms Used for Prediction of Melanoma

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      Pages 13-22

      Meta-learning via Search Combined with Parameter Optimization

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      Pages 23-32

      Flexible Multidiscretizer Based on Measures which are Used in Induction of Decision Trees

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      Pages 33-42

      Decision Tree Builder and Visualizer

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      Pages 43-56

      Modeling User Behavior by Integrating AQ Learning with a Database: Initial Results

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      Pages 57-66

      A Soft Decision Tree

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      Pages 67-76

      Agent-based Fuzzy Classifier System

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      Pages 77-90

      Decision Trees Learning System

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      Pages 91-100

      Discovering Interesting Rules From Dense Data

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      Pages 101-108

      Action-Rules, Re-Classification of Objects and e-Commerce

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      Pages 109-119

      Discovering Interesting Rules from Financial Data

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      Pages 121-130

      Bagging and Induction of Decision Rules

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      Pages 131-140

      Storing Data in KDD Systems /from Inlen 3.0 to InlenStar. Evolution of Database/

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      Pages 141-144

      Content Extraction Based on MPEG-7 Audio Representation

  3. Neural Network and Biologically Motivated Systems

    1. Front Matter

      Pages 145-145

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      Pages 147-156

      Ant Colony Programming for Approximation Problems

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      Pages 157-164

      Modification of Method of Least Squares for Tutoring a Neural Networks

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      Pages 165-174

      The Concept of Discoveries in Evolving Neural Net

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      Pages 175-183

      Searching for Memory in Artificial Immune System

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      Pages 185-194

      Selection Schemes in Evolutionary Algorithms

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      Book Chapter

      Pages 195-200

      Comparison of Crossover Operators for the State Assignment Problem

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