Good Classification Measures and How to Find Them

This repository contains supplementary materials for the paper "Good Classification Measures and How to Find Them" (NeurIPS 2021).

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How can I run it?

To run the experiments, you will need numpy, and scikit-learn libraries.

Use the input data files, provided in /data folder, and these scripts:

• binary_indicies_bruteforce.py [<num_of_items, default=5>] -- to reproduce the table N3
• meteo_inversion_matrix.py [full|10m|2h] -- to reproduce tables N4, N10, N11
• multiclass_indicies_imagenet.py -- to reproduce tables N5 and N12
• multiclass_indicies_sst.py -- to reproduce the table N6
• multiclass_indicies_yeast.py -- to reproduce tables N13 and N14