Homogenous Granulation and Its Epsilon Variant
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 an...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-05-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/8/2/36 |
| _version_ | 1817989557970272256 |
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| author | Krzysztof Ropiak Piotr Artiemjew |
| author_facet | Krzysztof Ropiak Piotr Artiemjew |
| author_sort | Krzysztof Ropiak |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T00:47:32Z |
| format | Article |
| id | doaj.art-f987223717a34b52bc6d7774cc4f6ce6 |
| institution | Directory Open Access Journal |
| issn | 2073-431X |
| language | English |
| last_indexed | 2024-04-14T00:47:32Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj.art-f987223717a34b52bc6d7774cc4f6ce62022-12-22T02:21:56ZengMDPI AGComputers2073-431X2019-05-01823610.3390/computers8020036computers8020036Homogenous Granulation and Its Epsilon VariantKrzysztof Ropiak0Piotr Artiemjew1Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, 10-710 Olsztyn, PolandFaculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, 10-710 Olsztyn, PolandIn 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.https://www.mdpi.com/2073-431X/8/2/36homogenous granulationRough Setsdecision systemsclassification |
| spellingShingle | Krzysztof Ropiak Piotr Artiemjew Homogenous Granulation and Its Epsilon Variant Computers homogenous granulation Rough Sets decision systems classification |
| title | Homogenous Granulation and Its Epsilon Variant |
| title_full | Homogenous Granulation and Its Epsilon Variant |
| title_fullStr | Homogenous Granulation and Its Epsilon Variant |
| title_full_unstemmed | Homogenous Granulation and Its Epsilon Variant |
| title_short | Homogenous Granulation and Its Epsilon Variant |
| title_sort | homogenous granulation and its epsilon variant |
| topic | homogenous granulation Rough Sets decision systems classification |
| url | https://www.mdpi.com/2073-431X/8/2/36 |
| work_keys_str_mv | AT krzysztofropiak homogenousgranulationanditsepsilonvariant AT piotrartiemjew homogenousgranulationanditsepsilonvariant |