[ https://issues.apache.org/jira/browse/SPARK-2163?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gang Bai resolved SPARK-2163. ----------------------------- 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. -- This message was sent by Atlassian JIRA (v6.2#6252)