Hi there, if you are interested in visualising data stream learning results, currently the best aapproach is to use CapyMOA https://github.com/adaptive-machine-learning/CapyMOA
Particularly, the tutorials for CapyMOA include examples on how to visualize Classification, Regression, Prediction Intervals and more! https://capymoa.org/tutorials.html
A simple python script to plot results overtime for a data stream marking drifts (both abrupt and gradual).
The plotline(...) was created to generate the plots for the MOA tutorial 'Simulating Concept in MOA'.
There are two examples on how to use it in the drift_stream_plot.py file.
The MOA tutorial can be found in here: https://moa.cms.waikato.ac.nz/tutorial-5-simulating-concept-drift-in-moa/
To successfully run this script you will need python 2 (it might fail on python 3). Also, you need matplotlib to generate the plots.