Metadata-Version: 2.1
Name: mlplot
Version: 0.0.0
Summary: UNKNOWN
Home-page: https://github.com/sbarton272/mlplot
Author: sbarton272
License: MIT License
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Requires-Dist: matplotlib (==2.2.3)
Requires-Dist: numpy (==1.15.1)
Requires-Dist: scipy (==1.1.0)
Requires-Dist: scikit-learn (==0.19.2)

[![CircleCI](https://circleci.com/gh/sbarton272/mlplot.svg?style=svg)](https://circleci.com/gh/sbarton272/mlplot)
[![Documentation Status](https://readthedocs.org/projects/mlplot/badge/?version=latest)](https://mlplot.readthedocs.io/en/latest/?badge=latest)

# mlplot

Machine learning evaluation plots using [matplotlib](https://matplotlib.org/) and [sklearn](http://scikit-learn.org/). [Check out the docs.](https://mlplot.readthedocs.io/)

## Install

```
pip install mlplot
```

ML Plot is runs with python 2.7, 3.5 and 3.6!

## Contributing

Create a PR!

# Plots

Starting from [sklearn](http://scikit-learn.org/stable/modules/model_evaluation.html).

## Classification

### ROC with AUC number
![ROC plot](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_roc.png)

### Calibration
![calibration plot](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_calibration.png)

### Precision-Recall
![precision recall curve plot](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_precision_recall.png)
![precision recall threshold plot](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_precision_recall_threshold.png)

### Population Histograms
![precision recall curve plot](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_population_histogram.png)

### Confusion Matrix
![confusion matrix](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_confusion_matrix.png)

### Classification Report
![classification report](https://raw.githubusercontent.com/sbarton272/mlplot/master/tests/output/test_report_table.png)

## Regression

- Full report
  - Mean sqr error
  - Mean abs error
  - Target mean, std
  - R2
- Residual plot
- Scatter plot
- Histogram of regressor

## Library Cleanup

- Try in a notebook
- Multi-model comparison
- Report to generate multiple plots at once

# Development

## Publish to pypi

```
python setup.py sdist bdist_wheel
twine upload --repository-url https://pypi.org/ dist/*
```


