Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/3833#discussion_r22931811
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -61,20 +67,70 @@ class LogisticRegressionModel (
override protected def predictPoint(dataMatrix: Vector, weightMatrix:
Vector,
intercept: Double) = {
- val margin = weightMatrix.toBreeze.dot(dataMatrix.toBreeze) + intercept
- val score = 1.0 / (1.0 + math.exp(-margin))
- threshold match {
- case Some(t) => if (score > t) 1.0 else 0.0
- case None => score
+ // If dataMatrix and weightMatrix have the same dimension, it's binary
logistic regression.
+ if (dataMatrix.size == weightMatrix.size) {
+ val margin = dot(weights, dataMatrix) + intercept
+ val score = 1.0 / (1.0 + math.exp(-margin))
+ threshold match {
+ case Some(t) => if (score > t) 1.0 else 0.0
+ case None => score
+ }
+ } else {
+ val dataWithBiasSize = weightMatrix.size / (nClasses - 1)
+ val dataWithBias = if(dataWithBiasSize == dataMatrix.size) {
+ dataMatrix
+ } else {
+ assert(dataMatrix.size + 1 == dataWithBiasSize)
+ MLUtils.appendBias(dataMatrix)
+ }
+
+ val margins = Array.ofDim[Double](nClasses)
+
+ val weightsArray = weights match {
+ case dv: DenseVector => dv.values
+ case _ =>
+ throw new IllegalArgumentException(
+ s"weights only supports dense vector but got type
${weights.getClass}.")
+ }
+
+ var i = 0
+ while (i < nClasses - 1) {
+ var margin = 0.0
+ dataWithBias.foreachActive { (index, value) =>
+ if (value != 0.0) margin += value * weightsArray((i *
dataWithBiasSize) + index)
+ }
+ margins(i + 1) = margin
+ i += 1
+ }
+
+ /**
+ * Find the one with maximum margins. Note that `margins(0) == 0`.
+ *
+ * PS, if you want to compute the probabilities for each outcome
instead of the outcome
+ * with maximum probability, remember to subtract the maxMargin from
margins if maxMargin
+ * is positive to prevent overflow.
+ */
+ var label = 0.0
+ var max = margins(0)
--- End diff --
Can this whole stanza be `margins.indexOf(margins.max)`? Granted that needs
two passes, but this is a small collection.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
