[Retracted] Application Analysis of the Machine Learning Fusion Model in Building a Financial Fraud Prediction Model

Table 9

. Parameters list of DT model.

No.	Parameters name	Implication
1	Criterion	Set the impurity judgment method, with two criterion parameters: “gini” Gini coefficient and “entropy” information gain
2	splitter	Used to control the random option, with two input values: “best” and “random.”
3	max_depth	Set the maximum number of layers, generally starting from 3
4	min_samples_leaf	The number of training samples affects the occurrence of branching. The value is set small here