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fix prepare data, and add k-folds support#146

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lazarusA merged 1 commit intomainfrom
la/fixes_prepare_data
Sep 17, 2025
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fix prepare data, and add k-folds support#146
lazarusA merged 1 commit intomainfrom
la/fixes_prepare_data

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@lazarusA
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@BernhardAhrens

  • this brings back the old behaviour from prepare_data (now in split_data)
  • Adds a dispatch on split_data where if you pass a data::Tuple{Tuple, Tuple} we assume that the user has already preprocessed the data into (x_train, y_train) and (x_val, y_val), allowing for k-fold cross validation scenarios.

tested on the Q10 example 😄 .

@lazarusA lazarusA marked this pull request as ready for review September 17, 2025 09:21
@BernhardAhrens
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Here is the original question by @luancordeiro:
Is there a built-in way to run cross-validation (e.g., K-fold or time-blocked) in EasyHybrid? If not, could you share a minimal Julia example showing how to set this up—rebuilding the model per fold, training on the train split, and evaluating on the holdout? Any quick tips on seeding/shuffling and batch norm during CV would also help.

@lazarusA lazarusA merged commit 8d10a29 into main Sep 17, 2025
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@lazarusA lazarusA deleted the la/fixes_prepare_data branch October 7, 2025 06:07
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2 participants