Github user loachli commented on the pull request:
https://github.com/apache/spark/pull/3890#issuecomment-69555498
I have tested QWLQN in spark 1.1. Based on
org.apache.spark.mllib.optimization.LBFGS, I create another class
org.apache.spark.mllib.optimization.QWLQN. The main change is as follows:
// val lbfgs = new BreezeLBFGS[BDV[Double]](maxNumIterations,
numCorrections, convergenceTol)
val lbfgs = new BreezeOWLQN[BDV[Double]](maxNumIterations,
numCorrections, convergenceTol)
I used the same environment and the the same logic of the SPARK-5027's
comparsion test, only changed the optimizer,and get the follow result.
algorithm time accuracy
SVMWithLBFGS 1441s 86.22%
SVMWithQWLQN 1678s 86.5%
SVMWithQWLQN in spark 1.1 increases the accuracy by 0.32% in this test,but
the speed will be decreased by 16.4%
I also tested SVMWithQWLQN in spark 1.2, and spark 1.2 use different
version of breeze and the API of QWLQN is changed.
// val lbfgs = new BreezeLBFGS[BDV[Double]](maxNumIterations,
numCorrections, convergenceTol)
val lbfgs = new BreezeOWLQN[Int, BDV[Double]](maxNumIterations,
numCorrections, convergenceTol)
In spark 1.2 SVMWithQWLQN get the same accuracy as in spark 1.1
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