Implementation of simple stacking method. Desgined to
work with sklearn classifiers and regressor functions,
but will work with any classifier that has a 'fit', 'predict',
and 'score' function. The function also includes a novel
technique for pruning poor performing classifiers for brute
forcing attempts.
When setting up the stack pass a list of classifiers for each
level of the stack. IE
classifiers = [[ensemble.RandomForestRegressor(),
ensemble.AdaBoostRegressor(),
linear_model.LinearRegessor()],
[ensemble.RandomForestRegressor(),
...],
[linear_model.LinearRegressor()]]
-
Notifications
You must be signed in to change notification settings - Fork 0
License
mulroony/sdlearn
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
No description, website, or topics provided.
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published