Github user thunterdb commented on a diff in the pull request:
https://github.com/apache/spark/pull/11549#discussion_r55597240
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -569,9 +572,46 @@ class GeneralizedLinearRegressionModel private[ml] (
familyAndLink.fitted(eta)
}
+ private var trainingSummary: Option[GeneralizedLinearRegressionSummary]
= None
+
+ private[regression] def setSummary(summary:
GeneralizedLinearRegressionSummary): this.type = {
+ this.trainingSummary = Some(summary)
+ this
+ }
+
+ /**
+ * Gets summary of model on training set. An exception is
+ * thrown if `trainingSummary == None`.
+ */
+ @Since("2.0.0")
+ def summary: GeneralizedLinearRegressionSummary = trainingSummary match {
+ case Some(summ) => summ
+ case None =>
+ throw new SparkException(
+ "No training summary available for this
GeneralizedLinearRegressionModel",
+ new NullPointerException())
+ }
+
@Since("2.0.0")
override def copy(extra: ParamMap): GeneralizedLinearRegressionModel = {
copyValues(new GeneralizedLinearRegressionModel(uid, coefficients,
intercept), extra)
.setParent(parent)
}
}
+
+/**
+ * :: Experimental ::
+ * GeneralizedLinearRegressionModel results evaluated on a dataset.
+ *
+ * @param predictions dataframe outputted by the model's `transform`
method.
+ * @param predictionCol field in "predictions" which gives the prediction
of each instance.
+ * @param labelCol field in "predictions" which gives the true label of
each instance.
+ * @param featuresCol field in "predictions" which gives the features of
each instance as a vector.
+ */
+@Experimental
+@Since("2.0.0")
+class GeneralizedLinearRegressionSummary private[regression] (
+ @Since("2.0.0") @transient val predictions: DataFrame,
+ @Since("2.0.0") val predictionCol: String,
--- End diff --
Based on a private discussion with @jkbradley , we should not expose the
name of the columns in the public API. Users should be referring to the
original model to get access to the column. In `LinearRegressionSummary`, they
are passed around because they are required for metrics. We do not need them
here.
---
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