Validation of binary classifiers and data used to develop them
Project description
Probatus
Overview
Probatus is a python package that helps validate binary classification models and the data used to develop them. Main features:
- probatus.interpret provides shap-based model interpretation tools
- probatus.metric_volatility provides tools using bootstrapping and/or different random seeds to assess metric volatility/stability.
- probatus.sample_similarity to compare two datasets using resemblance modelling, f.e.
train
with out-of-timetest
. - probatus.feature_elimination.ShapRFECV provides cross-validated Recursive Feature Elimination using shap feature importance.
Installation
pip install probatus
Documentation
Documentation at ing-bank.github.io/probatus/.
Contributing
To learn more about making a contribution to probatus, please see CONTRIBUTING.md
.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
probatus-1.6.1.tar.gz
(68.8 kB
view hashes)
Built Distribution
probatus-1.6.1-py3-none-any.whl
(108.0 kB
view hashes)