问题描述
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)
解决方法
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