Abstract - Road Traffic Accident Is Very Serious Matter

1230 WordsJan 4, 20175 Pages
Abstract - Road Traffic Accident is very serious matter of life. The World Health Organization (WHO) reports that about 1.24 million people of the world die annually on the roads. The Institute for Health Metrics and Evaluation (IHME) estimated about 907,900, 1.3 million and 1.4 million deaths from road traffic injuries in 1990, 2010 and 2013, respectively. Uttar Pradesh in particular one of the state of India, experiences the highest rate of such accidents. Thus, methods to reduce accident severity are of great interest to traffic agencies and the public at large. In this paper, we applied data mining technologies to link recorded road characteristics to accident severity and developed a set of rules that could be used by the Indian…show more content…
Extensive data pre-processing resulted in a clean the dataset containing 1, 31,698 accidents instances with missing values. The class label (‘PredictAcc’) had two nominal values: ‘Yes’ and ‘No’. During data exploration, different numbers of attributes were selected by different feature selection techniques which are provided in WEKA. Naïve Bayes classifier is selected in WEKA for classification and prediction that whether the accident may occur (Yes) or not (No) with 7 attributes, including 6 independent variables and one dependent variable (the class-label attribute ‘PredictAcc’), were fed to explorer of WEKA. After that Naïve Bayes classifier was used, and an accuracy of 87.2527 % was achieved. In the second experiment, the number of attributes were increased to 8, including 7 independent variables and one dependent variable, an accuracy of 88.0613 % was achieved. In the third experiment, the number of attributes were increased to 13, including 12 independent variables and one dependent variable and accuracy of 89.4554 % was achieved. Experimental results of Naïve Bayes classifier are discussed in this section using the data mining tool WEKA. Traffic Accident data contains accident severity which represents the severity of the accident. The six kinds of accident severity are Injury, Fatal, Physical disabled, Property loss, Normal and Death. The data source for this research

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