确认sklearn.metrics模块中是否存在root_mean_squared_error函数: 在sklearn.metrics模块中,root_mean_squared_error并不是一个标准的函数名。通常,我们计算均方根误差(Root Mean Squared Error, RMSE)使用的是mean_squared_error函数,然后取平方根。例如: python from sklearn.metrics import mean_squared_error impo...
Describe the bug For the sklearn.metrics.root_mean_squared_log_error(y_true, y_pred) & sklearn.metrics.mean_squared_log_error(y_true, y_pred) evaluation metrics, if any of the values in y_true or y_pred are below 0, the following ValueEr...
fromsklearn.metricsimportmean_squared_error importcopy defPC_Cross_Validation(X,y,pc,cv): ''' x :光谱矩阵 nxm y :浓度阵 (化学值) pc:最大主成分数 cv:交叉验证数量 return : RMSECV:各主成分数对应的RMSECV PRESS :各主成分数对应的PRESS ...
We will be using Mean Squared Error loss function to train the network. Initial Learning rate set to 0.001 model = multi_gpu_model(model, gpus=4) model.compile(optimizer=RMSprop(lr=1e-3), loss='mse') Training While training we keep track of improvements on our model using Validation Loss...