Ascertaining the impact of balancing the flood dataset on the performance of classification based flood forecasting models for the northern districts of Bihar
by Vikas Mittal; T.V. Vijay Kumar; Aayush Goel
International Journal of Water (IJW), Vol. 15, No. 2, 2022

Abstract: Bihar is the most flood-affected state in India and the losses incurred amount to one-third of the total losses due to floods in India. These losses can be alleviated by designing models that forecast floods in real time. One such model exists that uses classification based machine learning techniques to forecast floods in northern district of Bihar. However, the flood dataset used was imbalanced, as the non-flooding instances far exceeded the flooding instances. This paper attempts to address this problem by balancing this data using oversampling techniques and thereafter use it for designing flood forecasting models. The objective of the paper is to ascertain whether balancing dataset improves the performance of classifiers. Experimental based comparison showed that the classifiers performed comparatively better on balanced dataset in terms of accuracy, precision, recall, F-measure and AUC-ROC. Further, dataset balanced using KMeans SMOTE resulted in the maximum improvement in the performance of all classifiers.

Online publication date: Mon, 17-Jul-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Water (IJW):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com