Granular Computing in Decision Approximation An Application of Rough Mereology /
This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusion...
| Published in: | Springer eBooks |
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| Main Authors: | , |
| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Series: | Intelligent Systems Reference Library,
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1007/978-3-319-12880-1 Перейти в каталог НБ ТГУ |
Table of Contents:
- Similarity and Granulation
- Mereology and Rough Mereology. Rough Mereological Granulation
- Learning data Classification. Classifiers in General and in Decision Systems
- Methodologies for Granular Reflections
- Covering Strategies
- Layered Granulation
- Naive Bayes Classifier on Granular Reflections
- The Case of Concept-Dependent Granulation
- Granular Computing in the Problem of Missing Values
- Granular Classifiers Based on Weak Rough Inclusions
- Effects of Granulation on Entropy and Noise in Data. - Conclusions
- Appendix. Data Characteristics Bearing on Classification.