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xgbod_example.py demo code execution generated strange warning messages #156

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kdlin opened this issue Jan 8, 2020 · 1 comment
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xgbod_example.py demo code execution generated strange warning messages #156

kdlin opened this issue Jan 8, 2020 · 1 comment

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@kdlin
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@kdlin kdlin commented Jan 8, 2020

I ran the xgbod_example.py demo code, https://github.com/yzhao062/pyod/blob/master/examples/xgbod_example.py. The following warning messages were displayed.

/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/pyod/models/base.py:349: UserWarning: y should not be presented in unsupervised learning.
"y should not be presented in unsupervised learning.")
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)
/Users/dlin/opt/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/iforest.py:247: FutureWarning: behaviour="old" is deprecated and will be removed in version 0.22. Please use behaviour="new", which makes the decision_function change to match other anomaly detection algorithm API.
FutureWarning)

Some of the issues include:

  1. It did not like the Y labels.
  2. Somehow iforest.py was called.
@yzhao062
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@yzhao062 yzhao062 commented Jan 15, 2020

Yes. This is expected. XGBOD is based on two parts: supervised xgboost model and unsupervised anomaly detection models. The latter does not need y; iforest is part of the unsupervised models.

what happens is we run a bunch of unsupervised models and use their outlier scores as the new features appended to the orignal feature space. Finally, xgboost is trained on the enhanced feature space.
@yzhao062 yzhao062 closed this Feb 19, 2020
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@yzhao062 @kdlin
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