mean_squared_error / mse 均方误差,常用的目标函数,公式为((y_pred-y_true)**2).mean()
model = Sequential() model.add(Dense(64, init='uniform', input_dim=10)) model.add(Activation('tanh')) model.add(Activation('softmax')) sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True) model.compile(loss='mean_squared_error', optimizer=sgd)