访问单个树估计器以预测梯度提升分类器估计器的值

Question

gbm0 = GradientBoostingClassifier(n_estimators=500, random_state=42)
%time modelfit(gbm0, X_train, y_train)
##model fit is a fucntion i wrote to create a report on gbm classifier
preds = np.stack([t.predict(X_valid) for t in gbm0.estimators_])

给出错误

----> 1 preds = np.stack([t.predict(X_valid) for t in gbm0.estimators_])
AttributeError: 'numpy.ndarray' object has no attribute 'predict'

如何访问单个树预测方法以查看预测？

Answer 1

数组estimators_结果是具有用于二元分类的形状(n_estimators, 1)。因此，您可以通过重塑来修复错误：

preds = np.stack([t.predict(X_valid) for t in gbm0.estimators_.reshape(-1)])