MLLytics 0.1.7

A library of tools for easier evaluation of ML models.

# MLLytics

## Installation instructions `pip install MLLytics` or `python setup.py install`

## Update pypi instructions (for me) Creates the package `python setup.py sdist bdist_wheel` Upload package `twine upload --repository pypi *version_files*`

## Future ### Improvements and cleanup * Allow figure size and font sizes to be passed into plotting functions * Comment all functions and classes * Add type hinting to all functions and classes (https://mypy.readthedocs.io/en/latest/cheat_sheet_py3.html) * Example guides for each function in jupyter notebooks

### Cosmetic * Fix size of confusion matrix * Check works with matplotlib 3 * Tidy up legends and annotation text on plots * Joy plots * Brier score for calibration plot

### Big push * Cross Validation and plots (also repeated cross-validation) * Scoring functions * MultiClassMetrics class to inherit from ClassMetrics and share common functions * More output stats in overviews * Update reliability plot https://machinelearningmastery.com/calibrated-classification-model-in-scikit-learn/ * Tests * Switch from my metrics to sklearn metrics where it makes sense? aka `fpr, tpr, thresholds = roc_curve(y[test], probas_[:, 1])` and more general macro/micro average metrics from: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html#sklearn.metrics.recall_score

## Contributing Authors * Scott Clay * David Sullivan