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carpentries-incubator / machine-learning-trees-python

Introduction to tree models with Python
https://carpentries-incubator.github.io/machine-learning-trees-python
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Visualisation to explain boosting #3

Open MelanieIStefan opened 2 years ago

MelanieIStefan commented 2 years ago
Visualisations that may help explain boosting I can think of two visualisations that may help with explaining boosting (though I am not sure how easy they would be to make). One is to show the same image with the 6 trees next to each other, but colour them by how many points have been correctly classified and how many have been missed (so far) for each of the 6 trees. This would maybe help us better see what goes on in tree 6. The second one is to create a composite image of all the decision boundaries that would illustrate the idea of the last step, where a weighted average is taken. Basically, there would be areas that are more or less orange and areas that are more or less blue, and it would (hopefully) be easy to see how the final decision surface comes about. (This may be an overly simplistic idea on my part, and it might turn out that this is not actually helpful. But may be worth a try). Again, I could give these a shot.
tompollard commented 2 years ago

Thanks @MelanieIStefan I agree this would be a useful addition. If you have time to look I'd appreciate your help. I'm also happy to have a go if you'd like me to.