This repo contains a two-page description of Random Forests suitable for legal audiences to interpret machine learning algorithms. The idea behind this project was to capture the statistical mechanics of Random Forests, to make the information easier to digest for non-technical (typically legal) audiences, towards the start and end of model development and deployment.
-
Notifications
You must be signed in to change notification settings - Fork 0
ishani-ss/random_forests_for_legal_audiences
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
A two-page description of Random Forests is provided, that is suitable for legal audiences to interpret machine learning algorithms.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published