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This repository has been archived by the owner on May 19, 2023. It is now read-only.
Is your feature request related to a problem? Please describe.
Add a method of splitting for a categorical features using bag sampling approach for tree based anomaly detection. Customize the node splitting to handle IP address, port, protocol … etc.
Additional context
This implementation will have dependencies on ExtraTreeRegression implementation of CuML.
The text was updated successfully, but these errors were encountered:
tzemicheal
changed the title
[FEA] Include handling categorical features in the anomaly detection module.
[FEA] Include handling of categorical features in the anomaly detection component.
Nov 9, 2020
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This issue has been labeled inactive-30d due to no recent activity in the past 30 days. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed. This issue will be labeled inactive-90d if there is no activity in the next 60 days.
This issue has been labeled inactive-90d due to no recent activity in the past 90 days. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed.
Is your feature request related to a problem? Please describe.
Add a method of splitting for a categorical features using bag sampling approach for tree based anomaly detection. Customize the node splitting to handle IP address, port, protocol … etc.
Additional context
This implementation will have dependencies on ExtraTreeRegression implementation of CuML.
The text was updated successfully, but these errors were encountered: