Granular computing in decision approximation [electronic resource] : an application of rough mereology / Lech Polkowski, Piotr Artiemjew.
Polkowski, Lech, author.; Artiemjew, Piotr, author.
2015
QA248
Available Online

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Title
Granular computing in decision approximation [electronic resource] : an application of rough mereology / Lech Polkowski, Piotr Artiemjew.
Author
Polkowski, Lech, author.
ISBN
9783319128801 electronic book
3319128809 electronic book
9783319128795
DOI
https://doi.org/10.1007/978-3-319-12880-1
Published
Cham : Springer, [2015]
Language
English
Description
1 online resource : illustrations.
Item Number
10.1007/978-3-319-12880-1 doi
Call Number
QA248
Dewey Decimal Classification
511.3/22
Summary
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 inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k?nearest neighbors and bayesian classifiers. Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.
Bibliography, etc. Note
Includes bibliographical references and indexes.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (viewed April 9, 2015).
Added Author
Artiemjew, Piotr, author.
Series
Intelligent systems reference library ; v. 77.
Available in Other Form
Print version: Polkowski, Lech. Granular computing in decision approximation. Cham, [Germany] ; Heidelberg, [Germany] : Springer International Publishing, c2015 9783319128795
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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.

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