Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7361#discussion_r34491461
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/RegressionMetrics.scala
---
@@ -53,14 +53,21 @@ class RegressionMetrics(predictionAndObservations:
RDD[(Double, Double)]) extend
)
summary
}
+ private lazy val SSerr = math.pow(summary.normL2(1), 2)
+ private lazy val SStot = summary.variance(0) * (summary.count - 1)
+ private lazy val SSreg = {
+ val yMean = summary.mean(0)
+ predictionAndObservations.map {
+ case (prediction, _) => math.pow(prediction - yMean, 2)
+ }.reduce(_ + _)
+ }
/**
- * Returns the explained variance regression score.
- * explainedVariance = 1 - variance(y - \hat{y}) / variance(y)
- * Reference: [[http://en.wikipedia.org/wiki/Explained_variation]]
+ * Returns the variance explained by regression.
+ * @see
[[https://en.wikipedia.org/wiki/Fraction_of_variance_unexplained]]
*/
def explainedVariance: Double = {
- 1 - summary.variance(1) / summary.variance(0)
+ SSreg / summary.count
--- End diff --
Agree with all that. The proportion is kind of redundant. This is going
beyond fixing the formula, and also 'fixing' it to return something more
consistent with its name. It's an experimental class so seems legitimate. +1
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