TY  - JOUR
T1  - The Application of Binary k-Means Clustering to Identify Groups of Road Traffic Accident’s
Factors in United Kingdom
AU - Atiqah Binti Hamzah, Nur AU - Binti Saharan, Sabariah AU - Long Kek, Sie 
JO  - Research Journal of Applied Sciences
VL  - 15
IS  - 4
SP  - 135
EP  - 138
PY  - 2020
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2020.135.138
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2020.135.138
KW  - Clustering
KW  -k-means clustering
KW  -binary data
KW  -similarities
KW  -road accidents
AB  - 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.
ER  -