Dynamic Adapting Window Independence Drift Detection (DAWIDD)
This repository contains the implementation of the methods proposed in the paper Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD) by Fabian Hinder, André Artelt and Barbara Hammer
- The Dynamic Adapting Window Independence Drift Detection (DAWIDD) is implemented in DAWIDD.py. If your want to use a different/custom test for independence, you have to overwrite the method
test_independence. - The Hellinger-Distance-Drift-Detection-Method (HDDDM) is implemented in HDDDM.py.
- The experiments for comparing different drift detection methods are implemented in experiments_driftdetectors.py.
Requirements
- Python >= 3.6
- Packages as listed in REQUIREMENTS.txt
Third party components
- kernel_two_sample_test.py is taken from GitHub and implements the kernel two-sample tests as in Gretton et al 2012 (JMLR).
How to cite
You can cite the version on TODO.