A method to draw decision boundaries.
Modes of operation:
- For 2D feature space and binary probabilistic classifier, probability surface is drawn
TODO: probability output for n_classes > 2
- For 2D feature space and a classifier that does not predict posteriors, hard boundary is shown.
TODO: when possible, use decision_function() method and project that onto surface.
- For multi-dimensional, a way to plot high-dimensional decision boundaries via Voronoi tesselation onto 2D. Based on work by Migut, G. and Worring, M. and Veenman, C. J.
TODO: implement alternative
Author: Dainis Boumber [email protected]
base code: https://stackoverflow.com/questions/37718347/plotting-decision-boundary-for-high-dimension-data
@Article{MigutDMKD2015, author = "Migut, G. and Worring, M. and Veenman, C. J.", title = "Visualizing Multi-Dimensional Decision Boundaries in 2D", journal = "Data Mining and Knowledge Discovery", year = "2015", url = "https://ivi.fnwi.uva.nl/isis/publications/2015/MigutDMKD2015", has_image = 1 }