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This repository has been archived by the owner on Aug 2, 2022. It is now read-only.
Is your feature request related to a problem? Please describe.
By default, the maximum number of features allowed per detector is 5. While that can be increased by dynamically adjusting the limit at the expense of precision/recall, is there any way to enable adding categorical features, beyond the current default requirement of each feature being a one-dimensional number?
Describe the solution you'd like
Currently, only one-dimensional numbers can be added in a detector as a feature. It would be nice to enable adding arrays as features, or categorical features.
Describe alternatives you've considered
Is this an inherent limitation of the Random Cut Forest implementation, or can this modification be achieved via tweaking a setting? If so, please add the corresponding setting in the documentation, or mention here as response.
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
By default, the maximum number of features allowed per detector is 5. While that can be increased by dynamically adjusting the limit at the expense of precision/recall, is there any way to enable adding categorical features, beyond the current default requirement of each feature being a one-dimensional number?
Describe the solution you'd like
Currently, only one-dimensional numbers can be added in a detector as a feature. It would be nice to enable adding arrays as features, or categorical features.
Describe alternatives you've considered
Is this an inherent limitation of the Random Cut Forest implementation, or can this modification be achieved via tweaking a setting? If so, please add the corresponding setting in the documentation, or mention here as response.
The text was updated successfully, but these errors were encountered: