How to normalize data in spark logistic regression?
standardscaler=StandardScaler().setInputCol("features").setOutputCol("Scaled_features") scaled_df=standardscaler.fit(transformed_df).transform(transformed_df) scaled_df.select("Scaled_features","_c30").show(1)