Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/9413#discussion_r43685991
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -471,6 +484,59 @@ class LinearRegressionSummary private[regression] (
predictions.select(t(col(predictionCol),
col(labelCol)).as("residuals"))
}
+ lazy val numInstances: Long = predictions.count()
+
+ lazy val dfe = if (model.getFitIntercept) {
+ numInstances - model.weights.size -1
+ } else {
+ numInstances - model.weights.size
+ }
+
+ lazy val devianceResiduals: Array[Double] = {
+ val weighted = if (model.getWeightCol.isEmpty) lit(1.0) else
sqrt(col(model.getWeightCol))
+ val dr =
predictions.select(col(model.getLabelCol).minus(col(model.getPredictionCol))
+ .multiply(weighted).as("weightedResiduals"))
+ .select(min(col("weightedResiduals")).as("min"),
max(col("weightedResiduals")).as("max"))
+ .take(1)(0)
+ Array(dr.getDouble(0), dr.getDouble(1))
+ }
+
+ lazy val seCoef: Array[Double] = {
+ if (diag.length == 1 && diag(0) == 0) {
+ throw new UnsupportedOperationException(
+ "No Std. Error coefficients available for this
LinearRegressionModel")
+ } else {
+ val rss = if (model.getWeightCol.isEmpty) {
+ meanSquaredError * numInstances
+ } else {
+ val t = udf { (pred: Double, label: Double, weight: Double) =>
+ math.pow(label - pred, 2.0) * weight }
+ predictions.select(t(col(model.getPredictionCol),
col(model.getLabelCol),
+
col(model.getWeightCol)).as("wse")).agg(sum(col("wse"))).take(1)(0).getDouble(0)
+ }
+ val sigma2 = rss / dfe
+ diag.map(_ * sigma2).map(math.sqrt(_))
+ }
+ }
+
+ lazy val tVals: Array[Double] = {
--- End diff --
`tValues`
---
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