Mahmoud Rawas created SPARK-16235: ------------------------------------- Summary: "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: 1.6.2, 1.6.1, 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