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I've recently ran into a small issue, which is the time it takes to dataiku to score a model.
As you can see in provided screenshot, it took the model roughly 9min to do everything from loading to saving, while the remainder 51min were spent in scoring it.
Is there anything I can do to speed this up? I imagine that, for a binary classification, it calculates the results using different cut-off thresholds, but I'm not sure.
The algorithm I am using is a custom python model, based on a standard scikit-learn algorithm which is BalancedRandomForest Classifier.
Any help would be appreciated.
Operating system used: Windows
@MarcioCoelho I have the same problem after upgrading DSS 9.0 to 10.0.4 on Linux. It happens across all visual ML models (Random Forests, XGBoost, LightGBM, etc).
The model is training a binary classifier. Training takes about 5 minutes, but the scoring is stuck for over an hour. I am using DSS's builtin environment for visual ML LightGBM.
Did you find a fix?