dtreeviz fails with IndexError for n_classes >= 11 about dtreeviz HOT 16 OPEN

See if you can set dtreeviz.color_blind_friendly_colors[30+1] = [c]*30 for some color c.

Worked, thanks :)
Had to change the NUM_BINS array as well

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ah. yeah, sorry. I should put a check in there but only 10 classes can be handled right now. we had to handpick the colors. sorry about that.

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Wow, quick response!

So there is nothing I can do at the moment?

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Nope :( sorry.

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Okay, let's hope for a quick solution in the bright future. Keep up the good work and thanks for the quick response.

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thanks :) I'd be happy to accept a pull request that increased the number of color palettes ;)

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It's a bit more tricky than just having more colors.

get_num_bins gets called with n_classes as well and it references NUM_BINS which also only has 10 values.
What would be a good default value for NUM_BINS for n_classes > 10?

Any good ideas about having more colors?
Just repeating the colors and giving a warning, or making up new colors?

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Yeah, That's the problem. I started running out of ideas for colors and default values above 10. May be a sequential color map is required.

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Currently running into the same issue for an idea I am testing.
But totally understandable. Maybe a semi-simple and quick workaround is just to declare a simple target to color hex dict or just allowing us to passing in a list of colors.

As in the user declares the targets to color dict on their end.

{0: "#fcba03", 1: "#a303a9"}

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Any solution? I even considered not using colors, but when I add None to the color_blind_friendly_colors array (colors.py), I get the following error:
color_map = {v: color_values[i] for i, v in enumerate(class_values)}

TypeError: 'NoneType' object is not subscriptable

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In principle, just add another list of colors so this works:

color_values = color_blind_friendly_colors[n_classes]

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In principle, just add another list of colors so this works:

color_values = color_blind_friendly_colors[n_classes]

I have 30 classes. I don't really care about colors, they can all be represented by the same color.
Can I make it work?

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See if you can set dtreeviz.color_blind_friendly_colors[30+1] = [c]*30 for some color c.

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Maybe allow to represent only certainty of the written class via the hue. Then you can either have hue="class_certainty" or hue="certainty", and it switches to hue="certainty" above 10 classes and probably drops a warning that it did.

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Hi folks, if you still need a solution for this issue, you can follow this PR #185

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@tlapusan tla, @parrt

Hi, I really appreciate the work making support on more classes.

I now have a 86 classes decision tree model. Is it any possible way to call decision_boundaries without color issue?( "Index Error")

Or It's a bad idea having 86 classes , should I make my classes smaller?

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