python - 错误：总数 使用 Stacking ensemble 进行分类模型时的迭代次数达到极限

Question

我想使用堆叠集成模型构建分类模型。

这是我的代码：

level0 = list()
level0.append(('log', LogisticRegression()))
level0.append(('rf', RandomForestClassifier(n_estimators=600, class_weight='balanced')))
level0.append(('xgb', XGBClassifier(scale_pos_weight = sum_neg/sum_pos)))
# define meta learner model
level1 = LogisticRegression(solver='lbfgs', max_iter=10000)
# define the stacking ensemble
model = StackingClassifier(estimators=level0, final_estimator=level1, cv=5)

model.fit(X_train, y_train.ravel()) 
y_pred = model.predict(X_test)

这是错误：

764: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)

我将 max_iter 增加到 10000 但它仍然会产生这个错误。

标签： pythonensemble-learning