Simplifying Hyperparameter Tuning in Online Machine Learning -- The spotRiverGUI

arXiv:2402.11594v1 Announce Type: new
Abstract: Batch Machine Learning (BML) reaches its limits when dealing with very large amounts of streaming data. This is especially true for available memory, handling drift in data streams, and processing new, unknown data. Online Machine Learning (OML) is an alternative to BML that overcomes the limitations of BML. OML is able to process data in a sequential manner, which is especially useful for data streams. The `river` package is a Python OML-library, which provides a …

abstract arxiv cs.ai cs.lg data data streams drift hyperparameter machine machine learning memory processing simplifying streaming streaming data true type