Comparison of Prediction Models for Road Deaths On Road Network

This paper presents to compare prediction models for road deaths on road network by data mining techniques. In this work, the classifier is selected from four prediction algorithms: Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Neural Network (NN). The dead injured and dead people data in road accident data set of the Ministry of Transport, Thailand from January to April 2021. It has up to 8,560 records 46 attributes. This research has measured performance models with accuracy, precision, recall, and f-measure. The comparative results showed that the accuracy of RF is the most appropriate for predicting road deaths on road network with accuracy 89%, precision 0.86, recall 0.89, and f-measure 0.85.