Github user MechCoder commented on a diff in the pull request:
https://github.com/apache/spark/pull/8197#discussion_r37136732
--- Diff: docs/ml-guide.md ---
@@ -801,6 +801,141 @@ jsc.stop();
</div>
+## Examples: Summaries for LogisticRegression.
+
+Once LogisticRegression is run on data, it is useful to extract statistics
such as the
+loss per iteration which will provide an intuition on overfitting and
metrics to understand
+how well the model has performed on training and test data.
+
+LogisticRegressionTrainingSummary provides an interface to access such
relevant information
+i.e the objectiveHistory and metrics to evaluate the performance on the
training data
+directly with very less code to be rewritten by the user.
+In the future, a method would be made available in the fitted
LogisticRegressionModel to obtain
+a LogisticRegressionSummary of the test data as well.
+
+This examples illustrates the use of LogisticRegressionTrainingSummary on
some toyData.
--- End diff --
The Scala / Java effect :P
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