kwargs = self.filter_sk_params(Sequential.evaluate, kwargs)
kwargs.update({"show_accuracy": True})
loss, accuracy = self.model.evaluate(X, y, **kwargs)
return accuracy
class KerasRegressor(BaseWrapper):
"""Implementation of the scikit-learn regressor API for Keras.
After Change
"""
kwargs = self.filter_sk_params(Sequential.evaluate, kwargs)
outputs = self.model.evaluate(X, y, **kwargs)
if type(outputs) is not list:
outputs = [outputs]
for name, output in zip(self.model.metrics_names, outputs):
if name == "acc":
return output
raise Exception("The model is not configured to compute accuracy. "
