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Better explain the source of randomness for tree based models

See original GitHub issue

We keep getting questions and issues which relate to the randomness of tree based (#12979 and some conversations on gitter for instance).

It’d be nice to have a nice explanation somewhere, explaining the source of randomness in these models.

For the prospective contributor: this may involve having to check out sklearn/tree/tree.py and sklearn/tree/*.pyx files.

Issue Analytics

State:
Created 5 years ago
Comments:7 (6 by maintainers)

Top GitHub Comments

1reaction

jnothmancommented, Jan 15, 2019

Some of this could be in the random_state description, but I suspect that when a user is surprised by the randomness of a random forest, there’s not much you can do but wait for them to gain more experience and erudition on their own.

0reactions

glemaitrecommented, Jan 8, 2020

Done

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