表 1. T staging model parameters.

T分期模型参数

Model	Modeling classifier	Parameters
1	DecisionTreeClassifier, MultinomialNB	Make_union (make_pipeline (StackingEstimator (estimator=DecisionTreeClassifier (criterion=“entropy”, max_depth=5, min_samples_leaf=8, min_samples_split=8)), Binarizer (threshold=0.6000000000000001 )), make_union (FunctionTransformer (copy), FunctionTransformer (copy))), MultinomialNB (alpha=1.0, fit_prior=True)
2	MultinomialNB	MinMaxScaler (), StackingEstimator (estimator=MultinomialNB (alpha=10.0, fit_prior=True)), Binarizer (threshold=0.6000000000000001), StackingEstimator (estimator=MultinomialNB (alpha=10.0, fit_prior=False)), MultinomialNB (alpha=1.0, fit_prior=True)
3	MultinomialNB, DecisionTreeClassifier	StackingEstimator (estimator=MultinomialNB (alpha=10.0, fit_prior=True)), Binarizer (threshold=0.6000000000000001), StackingEstimator (estimator=DecisionTreeClassifier (criterion=“entropy”, max_depth=5, min_samples_leaf=17, min_samples_split=3)), MultinomialNB (alpha=1.0, fit_prior=True)
4	MultinomialNB, DecisionTreeClassifier	StackingEstimator (estimator=MultinomialNB (alpha=100.0, fit_prior=False)), Normalizer (norm="max"), StackingEstimator (estimator=DecisionTreeClassifier (criterion=“entropy”, max_depth=2, min_samples_leaf=16, min_samples_split=20)), MultinomialNB (alpha=1.0, fit_prior=True)
5	MultinomialNB	Binarizer (threshold=0.6000000000000001), RobustScaler (), Binarizer (threshold=0.65), MultinomialNB (alpha=1.0, fit_prior=True)