Metadata-Version: 2.4
Name: modelens
Version: 0.1.5
Summary: Diagnostic lens for binary classification ML models
Home-page: https://github.com/Ramlen/modelens
Author: Ramlen
Author-email: lvgajval@yandex.ru
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.20
Requires-Dist: matplotlib>=3.4
Requires-Dist: seaborn>=0.11
Requires-Dist: scikit-learn>=1.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# modelens

**Model Lens** — diagnostic dashboard for binary classification models.

One function call gives you the full picture:

- Loss curve (CatBoost / XGBoost / LightGBM)
- Score distribution histograms (train + test)
- Confusion matrix
- ROC curve with AUC
- Precision-Recall curves (all data + test, both classes)

## Installation

```bash
pip install modelens
