stream-learn -- open-source Python library for difficult data stream batch analysis

• URL: http://arxiv.org/abs/2001.11077v1
• Date: Wed, 29 Jan 2020 20:15:09 GMT
• Title: stream-learn -- open-source Python library for difficult data stream batch analysis
• Authors: Pawe{\l} Ksieniewicz, Pawe{\l} Zyblewski
• Abstract summary: stream-learn is compatible with scikit-learn and developed for the drifting and imbalanced data stream analysis. Main component is a stream generator, which allows to produce a synthetic data stream. In addition, estimators adapted for data stream classification have been implemented.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: stream-learn is a Python package compatible with scikit-learn and developed for the drifting and imbalanced data stream analysis. Its main component is a stream generator, which allows to produce a synthetic data stream that may incorporate each of the three main concept drift types (i.e. sudden, gradual and incremental drift) in their recurring or non-recurring versions. The package allows conducting experiments following established evaluation methodologies (i.e. Test-Then-Train and Prequential). In addition, estimators adapted for data stream classification have been implemented, including both simple classifiers and state-of-art chunk-based and online classifier ensembles. To improve computational efficiency, package utilises its own implementations of prediction metrics for imbalanced binary classification tasks.

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