Overview of Concept Drifts Detection Methodology in Data Stream

Abstract

Real-time online applications and mobile data generate huge volume of data. There is a need to process this data into compact data structures and extract meaningful information. A number of approaches have been proposed in literature to overcome the issues of data stream mining. This chapter summarizes various issues and application techniques. The chapter is a guideline for research to identify the research issues and select the most appropriate method in order to detect and process novel class.

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

“…The inclusion and exclusion criteria draw the boundary line towards the study selection, which is essential to ensure an unbiased and quality search. (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, 2016Webb et al, , 2018 To investigate the existing CD handling approaches and determine their effectiveness and shortcomings for current and future trends. (Jameel et al, 2020(Jameel et al, , 2020Uddin 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;…”

“…Sometimes, these changes could be an unvarying progression, and sometimes it could be varying and non-steady progress (Harel et al, 2014;Dyer and Polikar, 2012). Continuous drift follows a systematic pattern; these patterns repeatedly occur after a specific time interval (Khamassi et al, 2019;Saurav et al, 2018). Unlike the sudden drift, the blip drift is a spike of a new concept from the previous concept and recalls the previous concept back abruptly.…”