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Therefore, I'm trying to train multiple models and use their statistical values.
However, I noticed a difference in behavior between simply collecting models using a for loop and using Joblib Parallel.
The for loop exhibits a large variance, whereas joblib's Parallel shows a much smaller variance. And the prediction trends also differ.
I would appreciate any advice you may have.
Environment
Operating system: linux
python = "~3.10"
gluonts = {extras = ["mxnet"], version = "^0.14.4"}
The text was updated successfully, but these errors were encountered:
Description
I couldn't control randomness when training the model using DeepAR as follows:
Therefore, I'm trying to train multiple models and use their statistical values.
However, I noticed a difference in behavior between simply collecting models using a for loop and using Joblib Parallel.
The for loop exhibits a large variance, whereas joblib's Parallel shows a much smaller variance. And the prediction trends also differ.
I would appreciate any advice you may have.
Environment
The text was updated successfully, but these errors were encountered: