[ https://issues.apache.org/jira/browse/SPARK-16235?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15352473#comment-15352473 ]
Sean Owen commented on SPARK-16235: ----------------------------------- [~mahmoudr] but MSE is an error metric for regression, not classification. Why would that be relevant here then? > "evaluateEachIteration" is returning wrong results when calculated for > classification model. > -------------------------------------------------------------------------------------------- > > Key: SPARK-16235 > URL: https://issues.apache.org/jira/browse/SPARK-16235 > Project: Spark > Issue Type: Bug > Affects Versions: 1.6.1, 1.6.2, 2.0.0 > Reporter: Mahmoud Rawas > > Basically within the mentioned function there is a code to map the actual > value which supposed to be in the range of \[0,1] into the range of \[-1,1], > in order to make it compatible with the predicted value produces by a > classification mode. > {code} > val remappedData = algo match { > case Classification => data.map(x => new LabeledPoint((x.label * 2) - > 1, x.features)) > case _ => data > } > {code} > the problem with this approach is the fact that it will calculate an > incorrect error for an example mse will be be 4 time larger than the actual > expected mse > Instead we should map the predicted value into probability value in [0,1]. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org