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Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review

Manzoor Ahmed Hashmani

Manzoor Ahmed Hashmani

Universiti Teknologi PETRONAS (UTP)Perak, Malaysia
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Hashmani, Manzoor Ahmed
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Syed Muslim Jameel

Syed Muslim Jameel

Universiti Teknologi PETRONAS (UTP)Perak, Malaysia
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Jameel, Syed Muslim
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Mobashar Rehman

Mobashar Rehman

Universiti Tunku Abdul Rahman PerakKampar, Malaysia
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Rehman, Mobashar
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Atsushi Inoue

Atsushi Inoue

Eastern Washington UniversityCheney, United States
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Inoue, Atsushi
  
02 feb 2021
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Categoria dell'articolo: Research-Article
Pubblicato online: 02 feb 2021
Pagine: 1 - 16
Ricevuto: 09 dic 2019
DOI: https://doi.org/10.21307/ijssis-2020-029
Parole chiave
© 2020 Manzoor Ahmed Hashmani et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Flow chart for systematic selection of relevant articles using PRISMA guideline.
Flow chart for systematic selection of relevant articles using PRISMA guideline.

Figure 2:

Six (6) phases of review protocol.
Six (6) phases of review protocol.

Research questions and their subsequent research objectives_

S.No. Research questions Research objectives References
1 What are the fundamentals of the Concept Drift (CD) issue? To provide an overview of the basics of CD and determine how CD fundamentals changed over time. Also, highlight CD measuring, quantification techniques, and possible ways to overcome CD. (Budiman et al., 2016; Iwashita et al., 2019; Jameel et al., 2020a, b, c; Budiman et al., 2017; Zang et al., 2014; Zliobaite et al., 2014; Kuncheva, 2004; Ghorbani et al., 2017; Gupta and Dhawan, 2019; Jensen et al., 2019; Nishida et al., 2008; Harel et al., 2014; Dyer and Polikar, 2012; Khamassi et al., 2019; Saurav et al., 2018; Dongre and Malik, 2014; Dariusz, 2010; Sayed et al., 2018; Wadewale and Desai, 2015; Brzezinski and Stefanowski, 2014a; Hoens et al., 2012; Jagadeesh Chandra Bose et al., 2011; Huang et al., 2013; Minku et al., 2010; Tsymbal, 2004; Gomes et al., 2011; Hoens et al., 2011; Webb et al., 2016, 2018) Total of 29 papers
2 Do the state of art approaches (for CD handling) are adequate for current and future computing trends? To investigate the existing CD handling approaches and determine their effectiveness and shortcomings for current and future trends. (Jameel et al., 2020, 2020; Uddin et al., 2019, September; Liu and Wang, 2010; van Schaik and Tapson, 2015; Budiman et al., 2016; Huang et al., 2012; Zhai et al., 2014; Xu and Wang, 2016; 2017; Khamassi et al., 2019; PAC learning model Kearns and Vazirani, 1994; Gama et al., 2004; Baena-Garcıa et al., 2006; Lavaire et al., 2015; Friedman and Rafsky, 1979; Spinosa et al., 2007; Zeira et al., 2004; Kifer et al., 2004; Demšar and Bosni´c, 2018; Page, 1954; Mouss et al., 2004; Yasumura et al., 2007; Freund and Schapire, 1997; Bach and Maloof, 2008; Bifet, 2009; Bifet and Gavalda, 2007; Nishida, 2008; Ross et al., 2012; Raza et al., 2014; Rouse, 2009; Ditzler and Polikar, 2013; Zliobaite et al., 2012; Huang, 2006; Liang et al., 2006; Lan et al., 2009; Liu et al., 2019; Krawczyk, 2015; Cao et al., 2015; Khamassi et al., 2015; Brzezinski and Stefanowski, 2012; Sidhu and Bhatia, 2018; Bifet et al., 2009; Wang et al., 2003; Brzezin´ski and Stefanowski, 2011; Brzezinski and Stefanowski, 2014b; Street and Kim, 2001) Total of 46 papers

Primary and derived search terms for relevant research paper elicitation_

Search Terms
Primary Concept Drift Online learning Machine Learning Adaptive model Big Data
Derived Nonstationary features Fast Learning Supervised Self-regulatory Continuous data
Variability and Veracity Real-Time Learning Unsupervised Dynamic model Stream data
Conceptual change Adaptive Learning Clustering Meta-Cognitive model Unbalanced data
Concept Shift Dynamic Learning Classification Robust model Complex data
Feature Variability Continuous Learning Regression Evolving stream
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Inglese
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