Welcome to monoboost’s documentation!

Monoboost is the first instance based classification algorithm that allows for partial monotonicity (i.e. some non-monotone features). It uses standard inequality constraints on the monotone features, and novel L1 cones to place sensible constraints on non-monotone features.

To install, simply use pip install monoboost. For full documentation you’ve come to the right place. For a brief overview, refer to the README file in the Github repository.

Contents:

• Theory
• Monoboost Examples
  • Basic Model Fitting
• API
  • Classes
  • Functions