Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery, 1st Edition

  • Published By:
  • ISBN-10: 159904983X
  • ISBN-13: 9781599049830
  • DDC: 004
  • Grade Level Range: College Freshman - College Senior
  • 344 Pages | eBook
  • Original Copyright 2008 | Published/Released October 2009
  • This publication's content originally published in print form: 2008

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Pattern Recognition has a long history of applications to data analysis in business, military and social economic activities. While the aim of pattern recognition is to discover the pattern of a data set, the size of the data set is closely related to the methodology one adopts for analysis. "Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery" tackles those data sets and covers a variety of issues in relation to intelligent data analysis so that patterns from frequent or rare events in spatial or temporal spaces can be revealed. This book brings together current research, results, problems, and applications from both theoretical and practical approaches.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Editorial Advisory Board.
Table of Contents.
Detailed Table of Contents.
1: Introduction.
2: Automatic Intelligent Data Analysis.
3: Random Fuzzy Sets.
4: Pattern Discovery in Gene Expression Data.
5: Using “Blackbox” Algorithms Such as TreeNET and Random Forests for Data-Mining and for Finding Meaningful Patterns, Relationships, and Outliers in Complex Ecological Data: An Overview, an Example Using Golden Eagle Satellite Data and an Outlook for a Promising Future.
6: A New Approach to Classification of Imbalanced Classes via Atanassov's Intuitionistic Fuzzy Sets.
7: Pattern Discovery from Huge Data Set: Methodologies.
8: Fuzzy Neural Networks for Knowledge Discovery.
9: Genetic Learning: Initialization and Representation Issues.
10: Evolutionary Computing.
11: Particle Identification Using Light Scattering: A Global Optimization Problem.
12: Exact Markov Chain Monte Carlo Algorithms and their Applications in Probabilistic Data Analysis and Inference.
13: Pattern Discovery from Huge Data Set: Applications.
14: Design of Knowledge Bases for Forward and Reverse Mappings of TIG Welding Process.
15: A Fuzzy Decision Tree Analysis of Traffic Fatalities in the U.S..
16: New Churn Prediction Strategies in Telecom Industry.
17: Intelligent Classification and Ranking Analyses Using CaRBS: Bank Rating Application.
18: Analysis of Individual Risk Attitude for Risk Management Based on Cumulative Prospect Theory.
19: Pattern Recovery from Small Data Set: Methodologies and Applications.
20: Neural Networks and Bootstrap Methods for Regression Models with Dependent Errors.
21: Financial Crisis Modeling and Prediction with a Hilbert-EMD-Based SVM Approach.
22: Virtual Sampling with Data Construction Method.
Compilation of References.
About the Contributors.