Granular Computing in Decision Approximation

An Application of Rough Mereology

Autor: Lech Polkowski, Piotr Artiemjew

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Editura: Springer International Publishing AG

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This book presents a study in knowledge discovery in data with knowledge understood as a set of rela...

Informații despre carte

Autor

Lech Polkowski, Piotr Artiemjew

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2016

Pagini

452

EAN

9783319366210

ISBN

3319366211

Enbook ID

15193850

Editura

Springer International Publishing AG

Greutate

7022

Dimensiuni

155 x 235 x 24

Descriere completă

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.

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Granular Computing in Decision Approximation

An Application of Rough Mereology

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