Data Mining, Rough Sets and Granular Computing
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a diffe...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Heidelberg
Physica
2002, 2002
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| Edition: | 1st ed. 2002 |
| 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:
- Granularity, Multi-valued Logic, Bayes’ Theorem and Rough Sets
- The Generic Rough Set Inductive Logic Programming (gRS-ILP) Model
- Possibilistic Data Analysis and Its Similarity to Rough Sets
- 4: Granular Computing
- Observability and the Case of Probability
- Granulation and Granularity via Conceptual Structures: A Perspective From the Point of View of Fuzzy Concept Lattices
- Granular Computing with Closeness and Negligibility Relations
- Application of Granularity Computing to Confirm Compliance with Non-Proliferation Treaty
- Basic Issues of Computing with Granular Probabilities
- Multi-dimensional Aggregation of Fuzzy Numbers Through the Extension Principle
- On Optimal Fuzzy Information Granulation
- Ordinal Decision Making with a Notion of Acceptable: Denoted Ordinal Scales
- A Framework for Building Intelligent Information-Processing Systems Based on Granular Factor Space
- 5: Rough Sets and Granular Computing
- GRS: A Generalized Rough Sets Model
- Structure of Upper and Lower ApproximationSpaces of Infinite Sets
- Indexed Rough Approximations, A Polymodal System, and Generalized Possibility Measures
- 1: Granular Computing — A New Paradigm
- Some Reflections on Information Granulation and its Centrality in Granular Computing, Computing with Words, the Computational Theory of Perceptions and Precisiated Natural Language
- 2: Granular Computing in Data Mining
- Data Mining Using Granular Computing: Fast Algorithms for Finding Association Rules
- Knowledge Discovery with Words Using Cartesian Granule Features: An Analysis for Classification Problems
- Validation of Concept Representation with Rule Induction and Linguistic Variables
- Granular Computing Using Information Tables
- A Query-Driven Interesting Rule Discovery Using Association and Spanning Operations
- 3: Data Mining
- An Interactive Visualization System for Mining Association Rules
- Algorithms for Mining System Audit Data
- Scoring and Ranking the Data Using Association Rules
- Finding Unexpected Patterns in Data
- Discovery of Approximate Knowledge in Medical Databases Based on Rough Set Model