我正在使用GridSearchCV来调整超参数。我还想将不同的指标相互比较:
def create_model(...
model.add(Dense(,..)
model.compile(..)
return model
model = KerasRegressor(build_fn=create_model, verbose=0)
grid_obj = GridSearchCV (estimator=model
, param_grid=hypparas
, n_jobs=1
, cv = 3
, scoring = ['explained_variance', 'neg_mean_squared_error', 'r2']
, refit = 'neg_mean_squared_error'
, return_train_score=True
, verbose = 2
)
grid_result = grid_obj.fit(X_train1, y_train1)
Afai了解到,对超参数进行了优化,以使其最适合neg_mean_squared_error
。但是我如何看待其他指标的表现,例如在评估时?最好是如果我可以在视觉上比较它们。