Data Mining and Computational Intelligence
The volume offers a comprehensive coverage of the recent advances in the application of soft computing and fuzzy logic theory to data mining and knowledge discovery databases. It focuses on some of the hardest, and yet unsolved, issues of data mining like understandability of patterns, finding compl...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Heidelberg
Physica
2001, 2001
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| Edition: | 1st ed. 2001 |
| Series: | Studies in Fuzziness and Soft Computing
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Data Mining with Neuro-Fuzzy Models
- Granular Computing in Data Mining
- Fuzzification and Reduction of Information - Theoretic Rule Sets
- Mining Fuzzy Association Rules in a Database Containing Relational and Transactional Data
- Fuzzy Linguistics Summaries via Association Rules
- The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for Data-Based Generation of Small Interpretable Rule Bases in High-Dimensional Search Spaces
- Discovering Knowledge from Fuzzy Concept Lattice
- Mining of Labeled Incomplete Data Using Fast Dimension Partitioning
- Mining a Growing Feature Map by Data Skeleton Modelling
- Soft Regression - A Data Mining Tool
- Some Practical Applications of Soft Computing and Data Mining
- Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search
- Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series