[ENH v2] Add partial fit to the correct branch for decisiontreeclassifier#54
[ENH v2] Add partial fit to the correct branch for decisiontreeclassifier#54adam2392 merged 7 commits intosubmodulev3from
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Signed-off-by: Adam Li <adam2392@gmail.com>
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@PSSF23 does this code affect the normal building process not via partial_fit
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it shouldn't. update_stack only exists when the initial_roots has content.
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The CI errors seem related to the code introduced: https://dev.azure.com/neurodata/neurodata/_build/results?buildId=590&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a&t=4bd2dad8-62b3-5bf9-08a5-a9880c530c94 |
PSSF23
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@adam2392 Yes, the classes param was not properly passed in by the CI, so it was expecting a different kind of error. We can remove the _check_partial_fit_first_call check, but then there might be other errors associated with partial_fit api.
By the way, the performance is improved with the new branch, about the same as streaming tree on its own now. So previously the inferior results might be due to some bug in submodulev2.
Can you elaborate? Perhaps we can move the check to a better place and then have everything pass? |
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It appears that they are testing all methods with fitting functions ( The checks for |
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For unit tests, sklearn had built-in checks for partial_fit from other streaming algorithms, so I didn't prepare any extra ones. We can add new ones as we see fit, but the existing ones should cover most situations.
Signed-off-by: Adam Li <adam2392@gmail.com>
I see. I took a look and all you have to do is validate the input parameters before running the partial fit check: 63637f7 |
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Do you want to add the support for |
Signed-off-by: Adam Li <adam2392@gmail.com>
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Kay merged! @PSSF23 feel free to open up a PR to enable this for the |
Supersedes: #50
Reference Issues/PRs
What does this implement/fix? Explain your changes.
Any other comments?