I'm new to Spark and I'm getting bad performance with classification methods
on Spark MLlib (worse than R in terms of AUC).
I am trying to put my own parameters rather than the default parameters.
Here is the method I want to use :
train(RDD<LabeledPoint> input,
int numIterations,
double stepSize,
double miniBatchFraction,
Vector initialWeights)
How to choose "numIterations" and "stepSize"?
What does miniBatchFraction mean?
Is initialWeights necessary to have a good model? Then, how to choose them?
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