Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101159105
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -915,6 +917,22 @@ class GeneralizedLinearRegressionSummary
private[regression] (
/** Number of instances in DataFrame predictions. */
private[regression] lazy val numInstances: Long = predictions.count()
+
+ /**
+ * Name of features. If the name cannot be retrieved from attributes,
+ * set default names to "V1", "V2", and so on.
+ */
+ @Since("2.2.0")
+ lazy val featureName: Array[String] = {
+ val featureAttrs = AttributeGroup.fromStructField(
+ dataset.schema(model.getFeaturesCol)).attributes
+ if (featureAttrs == None) {
--- End diff --
@imatiach-msft This makes sense. I now changed the code to mirror the same
logic. When attritubes are missing, the default name is set to be the feature
name with suffix "_0", "_1" etc.
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