Metadata-Version: 2.3
Name: interactive_classification_metrics
Version: 0.2.2
Summary: Interactive classification metrics
Project-URL: Homepage, https://github.com/davhbrown/interactive_classification_metrics
Project-URL: Issues, https://github.com/davhbrown/interactive_classification_metrics/issues
Author: David H. Brown
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: <3.11,>=3.8
Requires-Dist: bokeh==2.4.3
Requires-Dist: numpy>=1.21.5
Requires-Dist: pandas==1.4.2
Requires-Dist: py-mcc-f1==0.1.0
Requires-Dist: scikit-learn==1.0.2
Requires-Dist: scipy==1.7.3
Description-Content-Type: text/markdown

# Interactive classification metrics
Get an intuitive sense for the ROC curve and other binary classification metrics with this interactive visualization application.

Read the [README](https://github.com/davhbrown/interactive-classification-metrics) for more information.

## Install
```
pip install interactive-classification-metrics
```
New environment recommended. Python >=3.8, <3.11. Installs:
```
bokeh==2.4.3
numpy>=1.21.5
pandas==1.4.2
py_mcc_f1==0.1.0
scikit_learn==1.0.2
scipy==1.7.3
```

## Run the application with Bokeh server locally
```
run-app
```

Opens a web browser where you can use the application.

## Acknowledgments
Special thanks to Dr. Davide Chicco ([@davidechicco](https://github.com/davidechicco)) for valuable feedback on this project.
