Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/9413#discussion_r44254161
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -474,6 +487,75 @@ class LinearRegressionSummary private[regression] (
predictions.select(t(col(predictionCol),
col(labelCol)).as("residuals"))
}
+ /** Number of instances in DataFrame predictions */
+ lazy val numInstances: Long = predictions.count()
+
+ /** Degrees of freedom */
+ private val degreesOfFreedom: Long = if (model.getFitIntercept) {
+ numInstances - model.coefficients.size - 1
+ } else {
+ numInstances - model.coefficients.size
+ }
+
+ /**
+ * The weighted residuals, the usual residuals rescaled by
+ * the square root of the instance weights.
+ */
+ lazy val devianceResiduals: Array[Double] = {
--- End diff --
@jkbradley There is "residuals" already exist, so I call it
```devianceResiduals```. I agree your opinion about adding other types of
residuals later, so I think we can try to combine the two functions into one
with different arguments. We also need do some code clean up for
```LinearRegressionSummary``` due to redundant arguments, I can finish it in a
follow up PR. @mengxr
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