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Reliability prediction plays a significant role in risk assessment of engineering structures. Mathematically, the prediction task can be seen as a classification (regression) procedure. In this aspect, machine learning methods have recently shown their superior performance over others in various research domains. Random forest (RF) is distinguished for its robustness and high accuracy in modeling and prediction work. However, its application in the area of structural reliability has not beendoi:10.1051/matecconf/201824101023 fatcat:5wigiozhf5boxp3wvy5wgy7yny