Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12624#discussion_r61252164
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -834,43 +864,51 @@ object GeneralizedLinearRegressionModel extends
MLReadable[GeneralizedLinearRegr
/**
* :: Experimental ::
- * Summarizing Generalized Linear regression Fits.
+ * Summary of [[GeneralizedLinearRegression]] model and predictions.
*
* @param predictions predictions output by the model's `transform` method
- * @param predictionCol field in "predictions" which gives the prediction
value of each instance
* @param model the model that should be summarized
- * @param diagInvAtWA diagonal of matrix (A^T * W * A)^-1 in the last
iteration
- * @param numIterations number of iterations
- * @param solver the solver algorithm used for model training
*/
@Since("2.0.0")
@Experimental
class GeneralizedLinearRegressionSummary private[regression] (
@Since("2.0.0") @transient val predictions: DataFrame,
- @Since("2.0.0") val predictionCol: String,
- @Since("2.0.0") val model: GeneralizedLinearRegressionModel,
- private val diagInvAtWA: Array[Double],
- @Since("2.0.0") val numIterations: Int,
- @Since("2.0.0") val solver: String) extends Serializable {
+ model: GeneralizedLinearRegressionModel) extends Serializable {
import GeneralizedLinearRegression._
- private lazy val family = Family.fromName(model.getFamily)
- private lazy val link = if (model.isDefined(model.getParam("link"))) {
+ // Extract values from model immediately to avoid problems with user
reseting model Params.
+ // Coefficients is not a deep copy, but that is acceptable.
+
+ /**
+ * Field in "predictions" which gives the prediction value of each
instance
+ */
+ @Since("2.0.0")
+ val predictionCol: String = model.getPredictionCol
+
+ private val weightCol: String = model.getWeightCol
+ private val labelCol: String = model.getLabelCol
+
+ private[regression] val familyName: String = model.getFamily
+ private[regression] val family: Family = Family.fromName(familyName)
+ private[regression] val link: Link = if (model.isDefined(model.link)) {
Link.fromName(model.getLink)
} else {
family.defaultLink
}
+ private[regression] val fitIntercept: Boolean = model.getFitIntercept
+ private[regression] val intercept: Double = model.intercept
+ private[regression] val coefficients: Vector = model.coefficients
--- End diff --
If the model of ```GeneralizedLinearRegressionSummary``` is immutable, it's
not necessary to extract these values in advance.
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