Hi!
I want to normalize features before train logistic regression. I setup scaler:
scaler2 = StandardScaler(withMean=True, withStd=True).fit(features)
and apply it to a dataset:
scaledData = dataset.map(lambda x: LabeledPoint(x.label,
scaler2.transform(Vectors.dense(x.features.toArray()
Hi Denys,
I don't see any issue in your python code, so maybe there is a bug in
python wrapper. If it's in scala, I think it should work. BTW,
LogsticRegressionWithLBFGS does the standardization internally, so you
don't need to do it yourself. It worths giving it a try!
Sincerely,
DB Tsai
