A review on classification of imbalanced data for wireless sensor networks

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 int...

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Bibliographic Details
Published inInternational Journal of Distributed Sensor Networks Vol. 16; no. 4; p. 155014772091640
Main Authors Patel, Harshita, Singh Rajput, Dharmendra, Thippa Reddy, G, Iwendi, Celestine, Kashif Bashir, Ali, Jo, Ohyun
Format Book Review Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.04.2020
Wiley
Subjects
Wireless sensor networks
imbalanced data
ensemble techniques
algorithm modification
data mining
data balancing
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Summary: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.
ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1177/1550147720916404