Abstract
Road accidents are now a common occurrence in our country. Every year thousands of people die in these accidents and thousands of people are crippled and cursed. Recently the level of road accidents has increased drastically. In this research paper, the authors discuss previous road accident history profoundly and predict death by applying the machine learning algorithm to get appropriate accuracy in Bangladesh. In this study, we had applied four classification models such as Decision Tree, K-Nearest Neighbors (KNN), Naïve Bayes and Logistic Regression to predict the death of road accidents in Bangladesh. The model was constructed, trained, and tested using the data from “Prothom Alo” newspaper, from which we collected 1237 road crash incidents. This research would be helpful for the policymakers and stakeholders related to the road to take the future steps with the highest accuracy of 88% in the Decision tree algorithm.
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Siddik, M.A.B., Arman, M.S., Hasan, A., Jahan, M.R., Islam, M., Biplob, K.B.B. (2021). Predicting the Death of Road Accidents in Bangladesh Using Machine Learning Algorithms. In: Singh, M., Tyagi, V., Gupta, P.K., Flusser, J., Ören, T., Sonawane, V.R. (eds) Advances in Computing and Data Sciences. ICACDS 2021. Communications in Computer and Information Science, vol 1441. Springer, Cham. https://doi.org/10.1007/978-3-030-88244-0_16
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DOI: https://doi.org/10.1007/978-3-030-88244-0_16
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