Login
Register
Reset Password
Publish & Distribute
Publishing Solutions
Distribution Solutions
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Blog
Contact
Search
EUR
USD
GBP
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Journal of Artificial Intelligence and Soft Computing Research
Volume 10 (2020): Issue 4 (October 2020)
Open Access
A Novel Drift Detection Algorithm Based on Features’ Importance Analysis in a Data Streams Environment
Piotr Duda
Piotr Duda
,
Krzysztof Przybyszewski
Krzysztof Przybyszewski
and
Lipo Wang
Lipo Wang
| Jun 15, 2020
Journal of Artificial Intelligence and Soft Computing Research
Volume 10 (2020): Issue 4 (October 2020)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Published Online:
Jun 15, 2020
Page range:
287 - 298
Received:
Nov 05, 2019
Accepted:
May 18, 2020
DOI:
https://doi.org/10.2478/jaiscr-2020-0019
Keywords
data stream mining
,
random forest
,
features importance
© 2020 Piotr Duda et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Piotr Duda
Department of Computer Engineering, Czestochowa University of Technology
Częstochowa, Poland
Krzysztof Przybyszewski
Information Technology Institute University of Social Sciences, Clark University,
Łódz
Lipo Wang
Nanyang Technological University, School of Electrical and Electronic Engineering
Singapore