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The anomaly detection flow for Auto-Sklearn disables the calculation of f for the training set, where we assume that the process will be unsupervised.
In order for the original test suite to pass, it would be better to add a switch-parameter for enabling anomaly detection on Auto-Sklearn. That way, the original tests should pass without any issues.
The text was updated successfully, but these errors were encountered:
johnantonn
changed the title
Add parameter for enabling anomaly detection
Auto-Sklearn: add parameter for enabling anomaly detection
Feb 9, 2022
For now, a pseudo-check was added to train_evaluator.py and automl.py to enable seamless integration with the original version of Auto-Sklearn. Later, this check needs to be controlled by a flag that will indicate normal execution or unsupervised anomaly detection for training PyOD classifiers.
The anomaly detection flow for Auto-Sklearn disables the calculation of f for the training set, where we assume that the process will be unsupervised.
In order for the original test suite to pass, it would be better to add a switch-parameter for enabling anomaly detection on Auto-Sklearn. That way, the original tests should pass without any issues.
The text was updated successfully, but these errors were encountered: