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].
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