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Performance Evaluation of Online Machine Learning Models Based on Cyclic Dynamic and Feature-Adaptive Time Series

Ahmed Salih AL-KHALEEFA, Rosilah HASSAN, Mohd Riduan AHMAD, Faizan QAMAR, Zheng WEN, Azana Hafizah MOHD AMAN, Keping YU

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Summary :

Machine learning is becoming an attractive topic for researchers and industrial firms in the area of computational intelligence because of its proven effectiveness and performance in resolving real-world problems. However, some challenges such as precise search, intelligent discovery and intelligent learning need to be addressed and solved. One most important challenge is the non-steady performance of various machine learning models during online learning and operation. Online learning is the ability of a machine-learning model to modernize information without retraining the scheme when new information is available. To address this challenge, we evaluate and analyze four widely used online machine learning models: Online Sequential Extreme Learning Machine (OSELM), Feature Adaptive OSELM (FA-OSELM), Knowledge Preserving OSELM (KP-OSELM), and Infinite Term Memory OSELM (ITM-OSELM). Specifically, we provide a testbed for the models by building a framework and configuring various evaluation scenarios given different factors in the topological and mathematical aspects of the models. Furthermore, we generate different characteristics of the time series to be learned. Results prove the real impact of the tested parameters and scenarios on the models. In terms of accuracy, KP-OSELM and ITM-OSELM are superior to OSELM and FA-OSELM. With regard to time efficiency related to the percentage of decreases in active features, ITM-OSELM is superior to KP-OSELM.

Publication
IEICE TRANSACTIONS on Information Vol.E104-D No.8 pp.1172-1184
Publication Date
2021/08/01
Publicized
2021/05/14
Online ISSN
1745-1361
DOI
10.1587/transinf.2020BDP0002
Type of Manuscript
Special Section PAPER (Special Section on Computational Intelligence and Big Data for Scientific and Technological Resources and Services)
Category

Authors

Ahmed Salih AL-KHALEEFA
  Imam Jafar Al-Sadiq University
Rosilah HASSAN
  Universiti Kebangsaan Malaysia (UKM)
Mohd Riduan AHMAD
  Universiti Teknikal Malaysia Melaka (UTeM)
Faizan QAMAR
  Universiti Kebangsaan Malaysia (UKM)
Zheng WEN
  Waseda University
Azana Hafizah MOHD AMAN
  Universiti Kebangsaan Malaysia (UKM)
Keping YU
  Waseda University

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