Github user BaiGang commented on a diff in the pull request:
https://github.com/apache/spark/pull/1104#discussion_r13910039
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala ---
@@ -195,4 +195,39 @@ class LBFGSSuite extends FunSuite with
LocalSparkContext with Matchers {
assert(lossLBFGS3.length == 6)
assert((lossLBFGS3(4) - lossLBFGS3(5)) / lossLBFGS3(4) <
convergenceTol)
}
+
+ test("Optimize via class LBFGS.") {
+ val regParam = 0.2
+
+ // Prepare another non-zero weights to compare the loss in the first
iteration.
+ val initialWeightsWithIntercept = Vectors.dense(0.3, 0.12)
+ val convergenceTol = 1e-12
+ val maxNumIterations = 10
+
+ val lbfgsOptimizer = new LBFGS(gradient, squaredL2Updater)
+ .setNumCorrections(numCorrections)
+ .setConvergenceTol(convergenceTol)
+ .setMaxNumIterations(maxNumIterations)
+ .setRegParam(regParam)
+
+ val weightLBFGS = lbfgsOptimizer.optimize(dataRDD,
initialWeightsWithIntercept)
+
+ val numGDIterations = 50
+ val stepSize = 1.0
+ val (weightGD, _) = GradientDescent.runMiniBatchSGD(
+ dataRDD,
+ gradient,
+ squaredL2Updater,
+ stepSize,
+ numGDIterations,
+ regParam,
+ miniBatchFrac,
+ initialWeightsWithIntercept)
+
+ // for class LBFGS and the optimize method, we only look at the weights
+ assert(compareDouble(weightLBFGS(0), weightGD(0), 0.02) &&
+ compareDouble(weightLBFGS(1), weightGD(1), 0.02),
+ "The weight differences between LBFGS and GD should be within 2%.")
+
--- End diff --
Thanks @mengxr , I'll correct the indentation and remove the empty line.
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