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Support Vector Machine with Principle Component Analysis for Road Traffic Crash Severity Classification

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Published under licence by IOP Publishing Ltd
, , Citation N.H.M. Radzi et al 2019 IOP Conf. Ser.: Mater. Sci. Eng. 551 012068 DOI 10.1088/1757-899X/551/1/012068

1757-899X/551/1/012068

Abstract

Road traffic crash (RTC) is one among the leading causes of death in the world, including Nigeria. It also turns many victims completely disabled and generally affected the socio–economic development in the society. In this paper, we proposed to predict the road crash severity injuries in Nigeria by identifying the most significant contributory factors using Principal Component Analysis with Support Vector Machine (SVM) used for classification algorithm. Road crash data from year 2013-2015 obtained from Federal Road Safety Corps Nigeria is used in this study. The result shows that and increased to 87% compared to 82% without feature selection.

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10.1088/1757-899X/551/1/012068