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examples/rolling_process_data/README.md
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@@ -4,9 +4,9 @@ This workflow is an example for `Rolling Process Data`.
## Background
When rolling train the models, data also needs to be generated in the different rolling windows. When the rolling window moves, the training data will also change, and the processor's learnable state (such as standard deviation, mean, etc.) will also be changed.
When rolling train the models, data also needs to be generated in the different rolling windows. When the rolling window moves, the training data will change, and the processor's learnable state (such as standard deviation, mean, etc.) will also change.
In order to avoid regenerating data, this example uses the `DataHandler-based DataLoader` to load the raw features that are not related to the rolling window, and then used Processors to generate processed-features related to the sliding window.
In order to avoid regenerating data, this example uses the `DataHandler-based DataLoader` to load the raw features that are not related to the rolling window, and then used Processors to generate processed-features related to the rolling window.
## Run the Code