Comparative Analysis of K-Nearest Neighbours Algorithm and Naive Bayes Algorithm for Prediction of Storm Warning

Challa Rohini, S. Kumar

2023

Abstract

The primary aim of this research was to enhance the accuracy of storm warnings by employing the novel K-Nearest Neighbours algorithm and comparing it to the Naive Bayes method. This investigation divided participants into two groups: the Novel K-Nearest Neighbours and the Naive Bayes Algorithm, each comprising ten representatives. The mean accuracy was determined using the ClinCalc software tool in a supervised learning setting, considering an alpha value of 0.05, a G-Power of 0.8, and a 95% confidence interval. The K-Nearest Neighbours algorithm showcased a notable accuracy rate of 68.20%, outstripping the 57.31% accuracy of the Naive Bayes. The difference between the two was statistically significant (p=0.000). In conclusion, the K-Nearest Neighbours approach substantially surpassed the Naive Bayes.

Paper Citation

in Harvard Style

Rohini C. and Kumar S. (2023). Comparative Analysis of K-Nearest Neighbours Algorithm and Naive Bayes Algorithm for Prediction of Storm Warning. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 103-108. DOI: 10.5220/0012569500003739

in Bibtex Style

@conference{ai4iot23,
author={Challa Rohini and S. Kumar},
title={Comparative Analysis of K-Nearest Neighbours Algorithm and Naive Bayes Algorithm for Prediction of Storm Warning},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={103-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012569500003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Comparative Analysis of K-Nearest Neighbours Algorithm and Naive Bayes Algorithm for Prediction of Storm Warning
SN - 978-989-758-661-3
AU - Rohini C.
AU - Kumar S.
PY - 2023
SP - 103
EP - 108
DO - 10.5220/0012569500003739
PB - SciTePress