Rough Mereology in Classification of Data: Voting by Means of Residual Rough Inclusions

Authors:
Lech Polkowski;Piotr Artiemjew
Affiliations:
Polish---Japanese Institute of IT, Warsaw, Poland;Department of Mathematics and Computer Science, University of Warmia and Mazury, Olsztyn, Poland
Venue:
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Year:
2008

Citing 4
Cited 0

Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
On the idea of using granular rough mereological structures in classification of data

RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
On classification of data by means of rough mereological granules of objects and rules

RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Rough mereological classifiers obtained from weak variants of rough inclusions

RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work, we pursue the theme of applications of rough mereology, presenting a scheme for classifier construction by voting of training objects, exhaustive set of rules, and granules of training objects according to weights assigned by residual rough inclusions. The results show a high effectiveness of this approach as witnessed by the reported tests with some well---known data sets from UCI repository whose results are compared against the standard rough set exhaustive classifier.