Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/15721#discussion_r93762729
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
---
@@ -1810,52 +1810,23 @@ class LogisticRegressionSuite
}
- test("binary logistic regression with weighted data") {
- val numClasses = 2
- val numPoints = 40
- val outlierData =
MLTestingUtils.genClassificationInstancesWithWeightedOutliers(spark,
- numClasses, numPoints)
- val testData = Array.tabulate[LabeledPoint](numClasses) { i =>
- LabeledPoint(i.toDouble, Vectors.dense(i.toDouble))
- }.toSeq.toDF()
- val lr = new
LogisticRegression().setFamily("binomial").setWeightCol("weight")
- val model = lr.fit(outlierData)
- val results = model.transform(testData).select("label",
"prediction").collect()
-
- // check that the predictions are the one to one mapping
- results.foreach { case Row(label: Double, pred: Double) =>
- assert(label === pred)
+ test("logistic regression with sample weights") {
+ def modelEquals(m1: LogisticRegressionModel, m2:
LogisticRegressionModel): Unit = {
+ assert(m1.coefficientMatrix ~== m2.coefficientMatrix absTol 0.01)
--- End diff --
Should we also check ```interceptVector```?
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