“…ML methods are more flexible with no or fewer model assumptions for input variables, and also have better fitting characteristics. Some of the commonly used ML approaches used in crash injury severity prediction include artificial neural networks (ANN) [ 58 , 59 , 60 ], random forest [ 54 , 61 , 62 ], support vector machines (SVM) [ 51 , 63 , 64 ], naïve Bayes [ 65 , 66 , 67 ], K-means clustering (KC) [ 68 , 69 , 70 ], and decision trees (DT) [ 71 , 72 , 73 ].…”