Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7655#discussion_r35480970
--- Diff: docs/mllib-metrics.md ---
@@ -0,0 +1,1464 @@
+---
+layout: global
+title: Evaluation Metrics - MLlib
+displayTitle: <a href="mllib-guide.html">MLlib</a> - Evaluation Metrics
+---
+
+* Table of contents
+{:toc}
+
+
+## Algorithm Metrics
+
+Spark's MLlib comes with a number of machine learning algorithms that can
be used to learn from and make predictions
+on data. When applying these algorithms, there is a need to evaluate their
performance on certain criteria, depending
--- End diff --
Nit, but maybe worth saying we're evaluating the output -- the model -- not
the algorithm itself. Evaluations also aren't a property of the application
that consumes the model, but of the model.
---
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.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
