Risk assessment method and device based on XGBoost and electronic equipment
A technology for risk assessment and risk, applied in digital data processing, payment system, agreement authorization, etc., to avoid overfitting, improve model accuracy, and improve the effect of evaluation
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Embodiment 1
[0047] Below, will refer to Figure 1 to Figure 3 An embodiment of the XGBoost-based risk assessment method of the present invention is described.
[0048] figure 1 It is a flowchart of the risk assessment method based on XGBoost of the present invention. Such as figure 1 As shown, a risk assessment method, the method includes the following steps.
[0049] Step S101, acquiring historical sample data, and determining positive and negative samples. The historical sample data includes user social data, user associated person data and fraud data.
[0050] Step S102, based on the acquired historical sample data, extract risk characteristic variables, and establish a training data set and a verification data set.
[0051] Step S103, screening risk characteristic variables according to screening rules.
[0052] Step S104, using the XGBoost algorithm to build a risk identification model and use the training data set for training.
[0053] Step S105, acquire the user social data ...
Embodiment 2
[0096] An apparatus embodiment of the present invention is described below, and the apparatus can be used to execute the method embodiment of the present invention. The details described in the device embodiments of the present invention should be regarded as supplements to the above method embodiments; details not disclosed in the device embodiments of the present invention can be implemented by referring to the above method embodiments.
[0097] refer to Figure 4 , Figure 5 and Figure 6 , the present invention also provides a risk assessment device 400 based on XGBoost, including: a data acquisition module 401, used to acquire historical sample data, determine positive and negative samples, the historical sample data includes user social data, user associated person data and fraud data; extraction module 402, based on the acquired historical sample data, extracts risk characteristic variables, and establishes training data set and verification data set; screening module...
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