Skip to content

numeristical/structureboost

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 

StructureBoost

StructureBoost is a package to do Gradient Boosting in a manner that exploits the structure of categorical variables.

Have you ever used "US state" as a variable in a prediction problem and thought "Why can't my algorithm use the geography of the states to make better predictions?"

Or you've used the month of the year as a predictor, but noticed that January should border December the same way that June borders July. (or hour of the day, or day of the week)

StructureBoost can help. Read the documentation and references below. Or dive into some examples

Video Lectures

There are some explanatory videos on the Numeristical Youtube Channel

Documentation

Read the Docs

References:

Lucena, B. "Exploiting Categorical Structure with Tree-Based Methods. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2949-2958, 2020. http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf

Lucena, B. "StructureBoost: Efficient Gradient Boosting for Structured Categorical Variables." https://arxiv.org/abs/2007.04446

About

Gradient boosting using categorical structure

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published