A review on classification of imbalanced data for wireless sensor networks

Harshita Patel, Dharmendra Singh Rajput, G Thippa Reddy, Celestine Iwendi, Ali Kashif Bashir and Ohyun Jo

International Journal of Distributed Sensor Networks, 2020, vol. 16, issue 4, 1550147720916404

Abstract: Classification of imbalanced data is a vastly explored issue of the last and present decade and still keeps the same importance because data are an essential term today and it becomes crucial when data are distributed into several classes. The term imbalance refers to uneven distribution of data into classes that severely affects the performance of traditional classifiers, that is, classifiers become biased toward the class having larger amount of data. The data generated from wireless sensor networks will have several imbalances. This review article is a decent analysis of imbalance issue for wireless sensor networks and other application domains, which will help the community to understand WHAT, WHY, and WHEN of imbalance in data and its remedies.

Keywords: Wireless sensor networks; data mining; imbalanced data; data balancing; algorithm modification; ensemble techniques (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:16:y:2020:i:4:p:1550147720916404

DOI: 10.1177/1550147720916404

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