Research Journal of Applied Sciences

Year: 2020
Volume: 15
Issue: 4
Page No. 135 - 138

The Application of Binary k-Means Clustering to Identify Groups of Road Traffic Accident’s Factors in United Kingdom

Authors : Nur Atiqah Binti Hamzah, Sabariah Binti Saharan and Sie Long Kek

Abstract: Cluster analysis is a formal study of methods and algorithms for natural grouping or clustering of objects according to measured or perceived intrinsic characteristics or similarities in each objects. The pattern of the each cluster and the relationship for each cluster were identified and then relate with the frequency of occurrence in the data set. This study aims to apply one of well-known clustering techniques, k-means clustering into binary data set in order to cluster the factors of road traffic accidents as the number of road accidents is increasing from day to day. Although there might be a list of expected factors that causing the road traffic accidents, none of us known which group of factors that has highest contribution that lead to road accident. By using k-means clustering, the patterns of road traffic accidents factors were identified.

How to cite this article:

Nur Atiqah Binti Hamzah, Sabariah Binti Saharan and Sie Long Kek, 2020. The Application of Binary k-Means Clustering to Identify Groups of Road Traffic Accident’s Factors in United Kingdom. Research Journal of Applied Sciences, 15: 135-138.

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