Data stream generation through real concept's interpolation
Joanna Komorniczak, Paweł Ksieniewicz · 2022
Among the recently published works in the field of data stream analysis -both in the context of classification task and concept drift detection -the deficit of real-world data streams is a recurring problem.This article proposes a method for generating data streams with given parameters based on real-world static data.The method uses onedimensional interpolation to generate sudden or incremental concept drifts.The generated streams were subjected to an exemplary analysis in the concept drift detection task with a detector ensemble.The method can potentially contribute to the development of methods focused on data stream processing.