Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4233#discussion_r24105867
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
---
@@ -462,6 +464,42 @@ class LogisticRegressionSuite extends FunSuite with
MLlibTestSparkContext with M
}
+ test("model save/load") {
+ // NOTE: This will need to be generalized once there are multiple
model format versions.
+ val nPoints = 20
+ val A = 2.0
+ val B = -1.5
+
+ val testData = LogisticRegressionSuite.generateLogisticInput(A, B,
nPoints, 42)
+ val testRDD = sc.parallelize(testData, 2)
+ testRDD.cache()
+
+ val lr = new LogisticRegressionWithLBFGS().setIntercept(true)
+ lr.optimizer.setNumIterations(1)
+ val model = lr.run(testRDD)
--- End diff --
Shall we construct a model directly? A unit test for model save/load should
not trigger training.
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