How does the PaddlePaddle framework handle missing and exceptional values?

In the PaddlePaddle framework, there are several typical methods for handling missing and outlier values.

1. Missing value processing: Typically, missing values can be filled using methods such as mean, median, mode, or interpolation. PaddlePaddle provides some useful functions for handling missing values, such as mean, median, mode, etc., in the paddle.impute module.
2. Outlier handling: Statistical methods or outlier detection algorithms such as Isolation Forest, One-Class SVM, Local Outlier Factor can be used to identify and deal with outliers. PaddlePaddle also offers some relevant functions and models, such as the detect_outlier function in the paddle.fluid.layers.outlier module.

When using the PaddlePaddle framework to process data, it is important to choose the appropriate method to handle missing and abnormal values based on the specific data situation in order to ensure the accuracy and stability of the model.