Treffer: Open-source Python repository for data drift analysis.

In this paper, we propose practical Python programs together with appropriate environments for the analysis of data stream drift, including the analysis of feature drift. The proposed approach contains a description of both, synthetic and real datasets. These datasets include different types of drifts like sudden, incremental, or gradual. Also, the location of the drift can be programmed. Additionally, we propose Java scripts that allow specifying the number and place of drift locations. The software is focused on prequential error methodology. Our proposition can be used by scientists interested in machine learning and concept drift detection because the proposed solution makes it easier to conduct practical experiments on that matter. The proposed solution allows for conducting experiments in a homogeneous programming environment. Versions of Python programs, stored in the GitHub repository, contain implementations of popular classifiers and drift detectors. The GitHub repository is located in the Public Domain. [ABSTRACT FROM AUTHOR]