Github user MechCoder commented on a diff in the pull request:
https://github.com/apache/spark/pull/8197#discussion_r37265276
--- Diff: docs/ml-guide.md ---
@@ -801,6 +801,153 @@ jsc.stop();
</div>
+## Examples: Summaries for LogisticRegression.
+
+Once
[`LogisticRegression`](api/scala/index.html#org.apache.spark.ml.classification.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`](api/scala/index.html#org.apache.spark.mllib.classification.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.
+
+This examples illustrates the use of `LogisticRegressionTrainingSummary`
on some toy data.
+
+<div class="codetabs">
+<div data-lang="scala">
+{% highlight scala %}
+import org.apache.spark.{SparkConf, SparkContext}
+import org.apache.spark.ml.classification.{LogisticRegression,
BinaryLogisticRegressionSummary}
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.sql.{Row, SQLContext}
+
+val conf = new SparkConf().setAppName("LogisticRegressionSummary")
+val sc = new SparkContext(conf)
--- End diff --
I copied the example code shown previously where all these are set.
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