Combining rough set-based relevance and redundancy for the ranking and selection of nominal features

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916680" target="_blank" >RIV/00216275:25410/20:39916680 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1877050920320561" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050920320561</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2020.09.156" target="_blank" >10.1016/j.procs.2020.09.156</a>

Result language
angličtina
Original language name
Combining rough set-based relevance and redundancy for the ranking and selection of nominal features
Original language description
In this paper, we propose a new method for features ranking and selection. Our approach is based on ranking nominal features in terms of their relevance to the assigned class and mutual redundancy with the other features. To calculate the relevance and redundancy, we propose to use a rough-set based approach. After performing the ranking, features filtering is carried out in a supervised way enabling the user to decide on the number of the retained features. The experiments revealed that thanks to our method, it is possible to filter out numerous features describing data while still maintaining satisfactory classification accuracy achieved by the classifier trained using the reduced dataset. The comparative experiments performed with the use of publicly available datasets proved the high efficiency and competitiveness of our approach.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GA19-15498S" target="_blank" >GA19-15498S: Modelling emotions in verbal and nonverbal managerial communication to predict corporate financial risk</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Procedia Computer Science : 24th KES International Conference on Knowledge-Based and Intelligent Information & Engineering Systems KES2020
ISBN
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ISSN
1877-0509
e-ISSN
—
Number of pages
10
Pages from-to
1459-1468
Publisher name
Elsevier Science BV
Place of publication
Amsterdam
Event location
ONLINE
Event date
Sep 16, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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