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Draft implementation of sample_weight for kmodes. #174

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merged 3 commits into from
Mar 30, 2022

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kklein
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@kklein kklein commented Mar 25, 2022

No description provided.

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coveralls commented Mar 25, 2022

Coverage Status

Coverage increased (+0.02%) to 97.925% when pulling 03a92c8 on kklein:kmodes_sample_weight into 4de7bf7 on nicodv:master.

@kklein kklein marked this pull request as ready for review March 25, 2022 17:22
@kklein kklein marked this pull request as draft March 25, 2022 17:52
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kklein commented Mar 25, 2022

Hi @nicodv ! Unfortunately I'm not able to recreate the test failure locally with python 3.10.4. Locally, both values in question amount to
242.05714285714285 and
242.05714285714288
respectively.

Do you have a hunch on what could be going on here?

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nicodv commented Mar 28, 2022

@kklein , I think it would be wise to use a static random seed to all your tests (random_state=42), just like here: https://github.com/nicodv/kmodes/blob/master/kmodes/tests/test_kprototypes.py#L68

I'm hoping it will eliminate any test failures due to random variations in the algorithms.

@kklein kklein marked this pull request as ready for review March 28, 2022 06:54
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LGTM, thank you for going the full stretch, @kklein !

@@ -495,17 +495,18 @@ def _k_prototypes_iter(Xnum, Xcat, centroids, cl_attr_sum, cl_memb_sum, cl_attr_
rindx = random_state.choice(choices)

cl_attr_sum, cl_memb_sum = _move_point_num(
Xnum[rindx], old_clust, from_clust, cl_attr_sum, cl_memb_sum
Xnum[rindx], old_clust, from_clust, cl_attr_sum, cl_memb_sum,
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Nice find, small oversight from last PR

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nicodv commented Mar 29, 2022

Please merge if you think it's ready, @kklein .

FYI, I'll be making a 0.12.0 release of kmodes after these additions.

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kklein commented Mar 30, 2022

Thanks for the fast review! :)
I think I don't have permission to merge this but from my side it's good to go!

@nicodv nicodv merged commit 247f193 into nicodv:master Mar 30, 2022
@nicodv nicodv mentioned this pull request Mar 30, 2022
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3 participants