Mean squared error (MSE) and mean squared logarithmic error (MSLE) are two loss functions that can have a significant impact on your data analyses. Here’s what you need to know to pick the right one.
1. RMSLE(Root Mean Square Logarithmic Error) 2. RMSPE(Root Mean Square Percentage Error) 对于数值序列出现长尾分布的情况,可以选择MSLE(Mean squared logarithmic error,均方对数误差),对原有数据取对数后再进行比较(公式中+1是为了避免数值为0时出现无穷值)。 0 3 R²系列 R²(R squared, Coefficient ...
Reference Issue: None What does this implement/fix? Explain your changes. This PR implements a new metric - "Mean Squared Logarithmic Error" (name truncated to mean_squared_log_error). I have adde...
any(): raise ValueError( "Root Mean Squared Logarithmic Error cannot be used when " "targets contain negative values." ) However, the actual calculations behind these errors are valid for values of y_true & y_pred larger than -1, so any values in y_true or y_pred that are in the ...
where\(\varvec{x}_{i}\)are the original image pixels,\(\varvec{y}_{i}\)are the restored samples and the number of image pixels isn. In order to better express the ability of filtering out impulses, arelaxedMean Squared Error measure (\(\text {MSE}_{\text {R}}\)) is used. ...
array([[0.5, 2], [1, 2.5], [8, 8]]) msle = mean_squared_log_error(y_true, y_pred, multioutput=[0.3, 0.7]) msle2 = mean_squared_error(np.log(1 + y_true), np.log(1 + y_pred), multioutput=[0.3, 0.7]) assert_almost_equal(msle, msle2, decimal=2) ...
Loss function: Mean Squared Error (MSE) was used as the loss function. Our implementation was written using MATLAB with GPU computing. 4.1.4. Stock Selection Once all the stock prices are successfully predicted, high-quality stocks are selected to perform in the optimization process one by one...