Practical Machine Learning for Streaming Data with Python: Design, Develop, and Validate Online Learning Models

© Sayan Putatunda 2021

S. PutatundaPractical Machine Learning for Streaming Data with Pythonhttps://doi.org/10.1007/978-1-4842-6867-4_2

2. Concept Drift Detection in Data Streams

Sayan Putatunda¹  

(1)

Bangalore, India

 

In the last chapter, you were introduced to streaming data, its applications, windowing techniques, and incremental and online learning algorithms. You were also introduced to the scikit-multiflow framework in Python and the various streaming data generators. This chapter discusses algorithms for concept drift detection in a streaming data context. It explores relevant techniques and how to implement them using the scikit-multiflow framework in Python.

Note

This chapter applies some of the scikit-multiflow framework’s (version 0.5.3) ...