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It is of great importance to identify the potential risks to the bank's loan customers. Based on data mining technology, it is an effective method to classify loan customers by classification algorithm. In this paper, we use Random Forest method, Logistic Regression method, SVM method and other suitable classification algorithms by python to study and analyze the bank credit data set, and compared these models on five model effect evaluation statistics of Accuracy, Recall, precision, F1-scoredoi:10.18535/ijsshi/v5i6.09 fatcat:mq5wzzmheffnfkajivrviqp74y