class StackingAveragedModels(BaseEstimator, RegressorMixin, TransformerMixin):
def __init__(self, base_models, meta_model, n_folds=5):
self.base_models = base_models
self.meta_model = meta_model
self.n_folds = n_folds
def fit(self, X, y):
self.base_models_ = [list() for x in self.base_models]
self.meta_model_ = clone(self.meta_model)
kfold = KFold(n_splits=self.n_folds, shuffle=True, random_state=156)
# train clones base models then create out-of-fold predictions
# that are needed to train the cloned meta-model
# 第一个循环，训练模型。第二个循环，验证
out_of_fold_predictions = np.zeros((X.shape[0], len(self.base_models)))
for i, model in enumerate(self.base_models):
for train_index, holdout_index in kfold.split(X, y):
instance = clone(model)
self.base_models_[i].append(instance)
instance.fit(X[train_index], y[train_index])
y_pred = instance.predict(X[holdout_index])
out_of_fold_predictions[holdout_index, i] = y_pred
# Now train the cloned meta-model using the out-of-fold predictions as new feature
self.meta_model_.fit(out_of_fold_predictions, y)
return self
# Do the predictions of all base models on the text data and use the averaged prediction as
# meta-feature for the final prediction which id done by meta-model
# 这是第二个阶段， 将第一阶段输出的值，当做特征，输入到第二阶段
def predict(self, X):
meta_features = np.column_stack([
np.column_stack([model.predict(X) for model in base_models]).mean(axis=1)
for base_models in self.base_models_])
return self.meta_model_.predict(meta_features)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-19-9601891919db> in <module>
----> 1 class StackingAveragedModels(BaseEstimator, RegressorMixin, TransformerMixin):
2 def __init__(self, base_models, meta_model, n_folds=5):
3 self.base_models = base_models
4 self.meta_model = meta_model
5 self.n_folds = n_folds
NameError: name 'BaseEstimator' is not defined
stackea_averaged_models = StackingAveragedModels(base_models=(ENet, GBoost, KRR),
meta_model=lasso)
score = rmsle_cv(stackea_averaged_models)
print("Stacking Averaged models score:{:.4f}({:.4f})\n".format(score.mean(), score.std()))
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-20-5cdaba2270ae> in <module>
----> 1 stackea_averaged_models = StackingAveragedModels(base_models=(ENet, GBoost, KRR),
2 meta_model=lasso)
3 score = rmsle_cv(stackea_averaged_models)
4 print("Stacking Averaged models score:{:.4f}({:.4f})\n".format(score.mean(), score.std()))
NameError: name 'StackingAveragedModels' is not defined
为什么会显示我未定义呢？
