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Data Mining and Computational Intelligence

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Cover of 'Data Mining and Computational Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Data Mining with Neuro-Fuzzy Models
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    Chapter 2 Granular Computing in Data Mining
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    Chapter 3 Fuzzification and Reduction of Information-Theoretic Rule Sets
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    Chapter 4 Mining Fuzzy Association Rules in a Database Containing Relational and Transactional Data
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    Chapter 5 Fuzzy Linguistic Summaries via Association Rules
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    Chapter 6 The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for Data-Based Generation of Small Interpretable Rule Bases in High-Dimensional Search Spaces
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    Chapter 7 Discovering Knowledge from Fuzzy Concept Lattice
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    Chapter 8 Mining of Labeled Incomplete Data Using Fast Dimension Partitioning
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    Chapter 9 Mining a Growing Feature Map by Data Skeleton Modelling
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    Chapter 10 Soft Regression — A Data Mining Tool
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    Chapter 11 Some Practical Applications of Soft Computing and Data Mining
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    Chapter 12 Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search
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    Chapter 13 Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series
Attention for Chapter 8: Mining of Labeled Incomplete Data Using Fast Dimension Partitioning
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Chapter title
Mining of Labeled Incomplete Data Using Fast Dimension Partitioning
Chapter number 8
Book title
Data Mining and Computational Intelligence
Published by
Physica, Heidelberg, January 2001
DOI 10.1007/978-3-7908-1825-3_8
Book ISBNs
978-3-79-082484-1, 978-3-79-081825-3
Authors

Bill C. H. Chang, Saman K. Halgamuge

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