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https://issues.apache.org/jira/browse/SPARK-2163?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Gang Bai resolved SPARK-2163.
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Resolution: Implemented
> Set ``setConvergenceTol'' with a parameter of type Double instead of Int
> ------------------------------------------------------------------------
>
> Key: SPARK-2163
> URL: https://issues.apache.org/jira/browse/SPARK-2163
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.0.0
> Reporter: Gang Bai
>
> The class LBFGS in mllib.optimization currently provides a
> {{setConvergenceTol(tolerance: Int)}} method for setting the convergence
> tolerance. The tolerance parameter is of type {{Int}}. The specified
> tolerance is then used as parameter in calling {{LBFGS.runLBFGS}}, where the
> parameter {{convergenceTol}} is of type {{Double}}.
> The Int parameter may cause problem when one creates an optimizer and sets a
> Double-valued tolerance. e.g:
> {code:borderStyle=solid}
> override val optimizer = new LBFGS(gradient, updater)
> .setNumCorrections(9)
> .setConvergenceTol(1e-4) // *type mismatch here*
> .setMaxNumIterations(100)
> .setRegParam(1.0)
> {code}
> IMHO there is no need to make the tolerance of type Int. Let's change it into
> a Double parameter and eliminate the type mismatch problem.
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