Next Article in Journal
An App that Changes Mentalities about Mobile Learning—The EduPARK Augmented Reality Activity
Next Article in Special Issue
Multilingual Ranking of Wikipedia Articles with Quality and Popularity Assessment in Different Topics
Previous Article in Journal
Detecting Website Defacements Based on Machine Learning Techniques and Attack Signatures
Previous Article in Special Issue
The Application of Ant Colony Algorithms to Improving the Operation of Traction Rectifier Transformers
Open AccessArticle

Homogenous Granulation and Its Epsilon Variant

Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, 10-710 Olsztyn, Poland
Author to whom correspondence should be addressed.
Extended version of paper “A Study in Granular Computing: homogenous granulation” presented at the 24rd International Conference on Information and Software Technologies (ICIST 2018), Vilnius, Lithuania, 5–6 October 2018.
These authors contributed equally to this work.
Computers 2019, 8(2), 36;
Received: 14 February 2019 / Revised: 28 April 2019 / Accepted: 7 May 2019 / Published: 10 May 2019
In the era of Big data, there is still place for techniques which reduce the data size with maintenance of its internal knowledge. This problem is the main subject of research of a family of granulation techniques proposed by Polkowski. In our recent works, we have developed new, really effective and simple techniques for decision approximation, homogenous granulation and epsilon homogenous granulation. The real problem in this family of methods was the choice of an effective parameter of approximation for any datasets. It was resolved by homogenous techniques. There is no need to estimate the optimal parameters of approximation for these methods, because those are set in a dynamic way according to the data internal indiscernibility level. In this work, we have presented an extension of the work presented at ICIST 2018 conference. We present results for homogenous and epsilon homogenous granulation with the comparison of its effectiveness. View Full-Text
Keywords: homogenous granulation; Rough Sets; decision systems; classification homogenous granulation; Rough Sets; decision systems; classification
Show Figures

Figure 1

MDPI and ACS Style

Ropiak, K.; Artiemjew, P. Homogenous Granulation and Its Epsilon Variant. Computers 2019, 8, 36.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop