Thanks Dhanesh, and how about the features question?
> 在 2017年3月19日，19:08，Dhanesh Padmanabhan 写道：
>
> Dhanesh
Thanks,
lujinhong
By the way, I found in spark 2.1 I can use setFamily() to decide binomial or
multinomial, but how can I do the same thing in spark 2.0.2?
If not support , which one is used in spark 2.0.2? binomial or multinomial?
> 在 2017年3月19日，18:12，jinhong lu 写道：
>
>
> I train my LogisticReg
I train my LogisticRegressionModel like this, I want my model to retain only
some of the features(e.g. 500 of them), not all the features. What shou I
do?
I use .setElasticNetParam(1.0), but still all the features is in
lrModel.coefficients.
import org.apache.spark.ml.classifi
Anyone help?
> 在 2017年3月13日，19:38，jinhong lu 写道：
>
> After train the mode, I got the result look like this:
>
>
> scala> predictionResult.show()
>
> +-++++--+
>
ents of x. A: 144109, x: 804202
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.linalg.BLAS$.gemv(BLAS.scala:521)
at
org.apache.spark.ml.linalg.Matrix$class.multiply(Matrices.scala:110)
at org.apache.spark.ml.linalg.DenseMatrix.multiply(Matrices.scala:176)
wh
Hi,
Since the DataSet will be the major API in spark2.0, why mllib will
DataFrame-based, and 'future development will focus on the DataFrame-based API.’
Any plan will change mllib form DataFrame-based to DataSet-based?
=
Thanks,
lujinhong
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