Hello everyone,
I am stuck with the (experimental, I think) API for machine learning
pipelines. I have a pipeline with just one estimator (ALS) and I want it to
try different values for the regularization parameter. Therefore I need to
supply an Evaluator that returns a value of type Double. I guess this could
be something like accuracy or mean squared error? The only implementation I
found is BinaryClassificationEvaluator, and I did not understand the
computation there.
I could not find detailed documentation so I implemented a dummy Evaluator
that just returns the regularization parameter:
new Evaluator {
def evaluate(dataset: DataFrame, paramMap: ParamMap): Double =
paramMap.get(als.regParam).getOrElse(throw new Exception)
}
I just wanted to see whether the lower or higher value "wins". On the
resulting model I inspected the chosen regularization parameter this way:
cvModel.bestModel.fittingParamMap.get(als.regParam)
And it was the highest of my three regularization parameter candidates.
Strange thing is, if I negate the return value of the Evaluator, that line
still returns the highest regularization parameter candidate.
So I am probably working with false assumptions. I'd be grateful if someone
could point me to some documentation or examples, or has a few hints to
share.
Cheers,
Stefan
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