Set of examples for scikit-learn self-learning.
This tutorial is being created. It is not finished.
The example shows how to compute basic classifier measures like precision, recall, f1
File: metrics.py
Examples explain how to interpret the precision-recall curve in an ideal, random case. What to do if the curve of two models looks similar.
File:
- precision-recall-curve.py
- precision-recall-curve_edge_case.py
- precision-recall-curve_model_comparision.py
- python > 3.6
- pipenv
- sklearn >0.21.3