GitHub user avulanov opened a pull request:
https://github.com/apache/spark/pull/1270
[MLLIB] SPARK-2329 Add multi-label evaluation metrics
Implementation of various multi-label classification measures, including:
Hamming-loss, strict and default Accuracy, macro-averaged Precision, Recall and
F1-measure based on documents and labels, micro-averaged measures:
https://issues.apache.org/jira/browse/SPARK-2329
This request relates to multi-class measures pull request:
https://github.com/apache/spark/pull/1155
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/avulanov/spark multilabelmetrics
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/1270.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1270
----
commit 154164bc3aef49158451e169c3e7ccc13d267e09
Author: Alexander Ulanov <[email protected]>
Date: 2014-06-30T10:33:25Z
Multilabel evaluation metics and tests: macro precision and recall averaged
by docs, micro and per-class precision and recall averaged by class
commit ad62df02fe47042d54a7a3d2347262e88bba01f0
Author: Alexander Ulanov <[email protected]>
Date: 2014-06-30T12:38:15Z
Comments and scala style check
commit 40593f5ac743feaa691e5ccdc0e6410d8dfa40d1
Author: Alexander Ulanov <[email protected]>
Date: 2014-06-30T15:28:56Z
Multi-label metrics: Hamming-loss, strict and normal accuracy, fix to macro
measures, bunch of tests
commit ca467652011b517b2c5f63d287e221964e27ded2
Author: Alexander Ulanov <[email protected]>
Date: 2014-06-30T15:38:26Z
Cosmetic changes: Apache header and parameter explanation
----
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
