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[MRG+1] Add sample_weight parameter to metrics.jaccard_similarity_score #3497

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[MRG+1] Add sample_weight parameter to metrics.jaccard_similarity_score #3497

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jatinshah
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  • Include this metric in sample_weight test in tests/test_common.py

@jatinshah
Add sample_weight parameter to metrics.jaccard_similarity_score
c0225ab 
 - Include this metric in sample_weight test in tests/test_common.py
@jatinshah jatinshah changed the title Add sample_weight parameter to metrics.jaccard_similarity_score #3450 Add sample_weight parameter to metrics.jaccard_similarity_score Jul 29, 2014
@jatinshah jatinshah mentioned this pull request Jul 29, 2014
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Coverage Status

Coverage decreased (-0.0%) when pulling c0225ab on jatinshah:master into e894205 on scikit-learn:master.

jnothman
jnothman reviewed Jul 29, 2014
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sklearn/metrics/classification.py
@@ -237,7 +238,7 @@ def confusion_matrix(y_true, y_pred, labels=None):
return CM


def jaccard_similarity_score(y_true, y_pred, normalize=True):
def jaccard_similarity_score(y_true, y_pred, normalize=True, sample_weight=None):
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Please limit line length to 79 chars, in accordance with PEP8

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OK, will fix.

@arjoly
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arjoly commented Jul 29, 2014

Could you document your improvement in the what's new?

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@arjoly Sure, can describe the improvements. Where is What's New located?

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Coverage increased (+0.0%) when pulling 6a2c60c on jatinshah:master into e894205 on scikit-learn:master.

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@arjoly - Any idea why the test is failing?

The detailed CI logs say that values with sample_weight=None and sample_weight=ones for unnormalized Jaccard are not same. The error log also displays the values as 105.20595238095238 and 105.20595238095237

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doc/whats_new.rst

On 29 July 2014 23:13, Coveralls [email protected] wrote:

[image: Coverage Status] https://coveralls.io/builds/1018844

Coverage increased (+0.0%) when pulling 6a2c60c
6a2c60c
on jatinshah:master into e894205
e894205
on scikit-learn:master.

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#3497 (comment)
.

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arjoly commented Jul 29, 2014

This looks some tests are checking assert equal instead of assert almost equal

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And this test does not fail on my local machine - so not sure what is going on.

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Is it ok to change the failing tests to assert almost equal instead of equal?

@jatinshah
Sample weight invariance tests check for almost equal
8f8c607 
- Replace sample weight invariance tests to check for
  almost equal instead of equal
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Coverage increased (+0.0%) when pulling 8f8c607 on jatinshah:master into cbcae04 on scikit-learn:master.

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Yes.

On 30 July 2014 14:14, Jatin Shah [email protected] wrote:

Is it ok to change the failing tests to assert almost equal instead of
equal?

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#3497 (comment)
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@jatinshah
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OK. It's done.

jnothman
jnothman reviewed Jul 30, 2014
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doc/whats_new.rst
............


- Add ``sample_weight`` parameter to `metrics.jaccard_similarity_score`.
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please include this under 0.16

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Coverage increased (+0.0%) when pulling 5c16096 on jatinshah:master into cbcae04 on scikit-learn:master.

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LGTM!

@jnothman jnothman changed the title Add sample_weight parameter to metrics.jaccard_similarity_score [MRG+1] Add sample_weight parameter to metrics.jaccard_similarity_score Jul 30, 2014
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arjoly commented Jul 30, 2014

Is it ok to change the failing tests to assert almost equal instead of equal?

The small variations are due to small floating point arithmetic errors. Asserting that 6 decimals (the default of assert_almost_equal) is enough to check correctness and equality in most cases.

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arjoly commented Jul 30, 2014

+1 I am going to merge by rebase !

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arjoly commented Jul 30, 2014

Merge by rebase 1b2833a. Thanks and congratulation for your first contribution.

@arjoly arjoly closed this Jul 30, 2014
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Thanks @arjoly.

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@jatinshah @coveralls @arjoly @jnothman