Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/8022#discussion_r37824754
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/classification/StreamingLogisticRegressionSuite.scala
---
@@ -184,4 +184,72 @@ class StreamingLogisticRegressionSuite extends
SparkFunSuite with TestSuiteBase
)
val output: Seq[Seq[(Double, Double)]] = runStreams(ssc, numBatches,
numBatches)
}
+
+ test("parameter accuracy with full memory (decayFactor = 1)") {
+
+ val nPoints = 100
+
+ // create model
+ val model = new StreamingLogisticRegressionWithSGD()
+ .setDecayFactor(1)
+ .setInitialWeights(Vectors.dense(0.0))
+ .setStepSize(0.5)
+ .setNumIterations(50)
+
+ // generate sequence of simulated data
+ val numBatches = 20
+ // the first few RDD's are generated under the model A
+ val inputA = (0 until (numBatches - 1)).map { i =>
+ LogisticRegressionSuite.generateLogisticInput(0.0, 0.5, nPoints, 42
* (i + 1))
+ }
+ // the last RDD is generated under the model B
+ val inputB =
+ LogisticRegressionSuite.generateLogisticInput(0.0, 1.5, nPoints, 42
* (numBatches + 1))
+ val input = inputA :+ inputB
+
+ // apply model training to input stream
+ ssc = setupStreams(input, (inputDStream: DStream[LabeledPoint]) => {
+ model.trainOn(inputDStream)
+ inputDStream.count()
+ })
+ runStreams(ssc, numBatches, numBatches)
+
+ // with full memory, the final parameter estimates should be close to
model A
+ assert(model.latestModel().weights(0) ~== 0.5 relTol 0.5)
--- End diff --
A 50% tolerance is quite large, can the tests still regularly pass with a
smaller tolerance?
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