在keras中的每个纪元后如何查看验证错误

Question

I am using keras to train a model for regression. My code looks like:

estimators = []
estimators.append(('standardize', StandardScaler()))
estimators.append(('mlp', KerasRegressor(build_fn=baseline_model, epochs=100, batch_size=32, verbose=2)))
pipeline = Pipeline(estimators)
X_train, X_test, y_train, y_test = train_test_split(X, Y,
                                                    train_size=0.75, test_size=0.25)
pipeline.fit(X_train, y_train)

The problem is that it is dramatically overfitting. How can I see the validation error after each epoch?

Answer 1

You can transmit parameters to KerasRegressor fit method:

validation_split: float (0. < x < 1). Fraction of the data to use as held-out validation data. validation_data: tuple (x_val, y_val) or tuple (x_val, y_val, val_sample_weights) to be used as held-out validation data. Will override validation_split.

via Pipeline fit method :

**fit_params : dict of string -> object Parameters passed to the fit method of each step, where each parameter name is prefixed such that parameter p for step s has key s__p.

Example:

pipeline.fit(X_train, y_train, mlp__validation_split=0.3)