Isolation Forest / Autoencoder contamination parameter not effecting results? #552
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yzhao062
DrSouthmountain
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Contamination does not change roc which is based on raw scores.
Contamination is only change threshold in to convert raw scores to binary
anomaly labels.
*Yue Zhao*
Assistant Professor
Department of Computer Science <https://www.cs.usc.edu/>
University of Southern California <https://www.usc.edu/>
1 412-877-7836 | ***@***.***
Homepage: https://viterbi-web.usc.edu/~yzhao010/
…On Wed, Apr 24, 2024 at 1:06 AM DrSouthmountain ***@***.***> wrote:
Hello,
I have have run Isolation Forest and Autoencoder methods on my own
datasets. I have tried to see what impact adjusting the contamination
parameter makes on the resulting ROC and precision. As far as I can see
nothing changes when adjusting the contamination parameter of the
classifier from 0.1 to 0.5 (or anything in between).
I have tried the same with the isolation_forest example file from the repo
(keeping the randomness stable by using the random_state parameter).
Has anyone else run into the same? Or am I misunderstanding things?
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Contamination does not change roc which is based on raw scores. Contamination is only change threshold in to convert raw scores to binary anomaly labels. |
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Hello,
I have have run Isolation Forest and Autoencoder methods on my own datasets. I have tried to see what impact adjusting the contamination parameter makes on the resulting ROC and precision. As far as I can see nothing changes when adjusting the contamination parameter of the classifier from 0.1 to 0.5 (or anything in between).
I have tried the same with the isolation_forest example file from the repo (keeping the randomness stable by using the random_state parameter).
Has anyone else run into the same? Or am I misunderstanding things?
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