Demo script for visualising behaviour, (dis)similarity or complementarity of binary classifiers in response to a common dataset.
The recipe itself is simple:
- compute rank correlation of scores (Kendall's tau)
- visualise with multidimensional scaling (MDS plot)
Kinnunen, T., Nautsch, A., Sahidullah, M., Evans, N., Wang, X., Todisco, M., Delgado, H., Yamagishi J, Lee, K.A.,
"Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing",
in Proc. Interspeech, 2021.
License: https://creativecommons.org/licenses/by/4.0/
After installing conda:
conda create -n classifier-adjacency python=3.7
conda activate classifier-adjacency
pip install sklearn matplotlib pandas h5py
git clone https://gitlab.eurecom.fr/nautsch/pybosaris pybosaris-source
ln -s pybosaris-source/pybosaris pybosaris
python classifier_adjacency_demo.py
This creates two tikz/pgfplot files:
asv.tikz
asv_legend.tikz
