<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Attribute reduction is a key issue in the research of rough sets. Aiming at the shortcoming of attribute reduction algorithm based on discernibility matrix, an attribute reduction method based on sample extraction and priority is presented. Firstly, equivalence classes are divided using quick sort for computing compressed decision table. Secondly, important samples are extracted from compressed decision table using iterative self-organizing data analysis technique algorithm(ISODATA). Finally, attribute reduction of sample decision table is conducted based on the concept of priority. Experimental results show that the attribute reduction method based on sample extraction and priority can significantly reduce the overall execution time and improve the reduction efficiency.</p>
</abstract>

Attribute reduction is a key issue in the research of rough sets. Aiming at the shortcoming of attribute reduction algorithm based on discernibility matrix, an attribute reduction method based on sample extraction and priority is presented. Firstly, equivalence classes are divided using quick sort for computing compressed decision table. Secondly, important samples are extracted from compressed decision table using iterative self-organizing data analysis technique algorithm(ISODATA). Finally, attribute reduction of sample decision table is conducted based on the concept of priority. Experimental results show that the attribute reduction method based on sample extraction and priority can significantly reduce the overall execution time and improve the reduction efficiency.

Attribute Reduction Method Based on Sample Extraction and Priority

Endicott College of International Studies

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Attribute Reduction Method Based on Sample Extraction and Priority"}

Attribute reduction is a key issue in the research of rough sets. Aiming at the shortcoming of attribute reduction algorithm based on discernibility matrix, an...

Attribute Reduction Method Based on Sample Extraction and Priority

Publié en ligne: 12 avr. 2021

Pages: 219 - 226

Reçu: 28 nov. 2020

Accepté: 31 janv. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00036

Mots clés
rough sets, sample extraction, priority, attribute reduction, algorithm

© 2021 Biqing Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Attribute Reduction Method Based on Sample Extraction and Priority

Publié en ligne: 12 avr. 2021

Pages: 219 - 226

Reçu: 28 nov. 2020

Accepté: 31 janv. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00036

Mots clésrough sets, sample extraction, priority, attribute reduction, algorithm

© 2021 Biqing Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
rough sets, sample extraction, priority, attribute reduction, algorithm