Re: Equivalent of "predict" function from LogisticRegressionWithLBFGS in OneVsRest with LogisticRegression classifier (Spark 2.0)

2016-08-29 Thread Nick Pentreath
Try this:

val df = spark.createDataFrame(Seq(Vectors.dense(Array(10, 590, 190,
700))).map(Tuple1.apply)).toDF("features")

On Sun, 28 Aug 2016 at 11:06 yaroslav  wrote:

> Hi,
>
> We use such kind of logic for training our model
>
> val model = new LogisticRegressionWithLBFGS()
>   .setNumClasses(3)
>   .run(train)
>
> Next, during spark streaming, we load model and apply incoming data to this
> model to get specific class, for example:
>
>model.predict(Vectors.dense(10, 590, 190, 700))
>
> How we could achieve the same logic for OneVsRest classification:
>
> val classifier = new LogisticRegression()
>   .setMaxIter(10)
>   .setTol(1E-6)
>   .setFitIntercept(true)
>
> val ovr = new OneVsRest().setClassifier(classifier)
> val model = ovr.fit(train)
>
> How call "predict" for this model with vector Vectors.dense(10, 590, 190,
> 700) and get class ?
>
> We try play with this:
>
> val df = spark.createDataFrame(Array((10, 590, 190, 700)))
> val pr_class = model.transform(df)
>
> but get error.
>
> Thank you.
>
>
>
>
>
>
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Equivalent of "predict" function from LogisticRegressionWithLBFGS in OneVsRest with LogisticRegression classifier (Spark 2.0)

2016-08-28 Thread yaroslav
Hi,

We use such kind of logic for training our model

val model = new LogisticRegressionWithLBFGS()
  .setNumClasses(3)
  .run(train)

Next, during spark streaming, we load model and apply incoming data to this
model to get specific class, for example:

   model.predict(Vectors.dense(10, 590, 190, 700))

How we could achieve the same logic for OneVsRest classification:

val classifier = new LogisticRegression()
  .setMaxIter(10)
  .setTol(1E-6)
  .setFitIntercept(true)

val ovr = new OneVsRest().setClassifier(classifier)
val model = ovr.fit(train)

How call "predict" for this model with vector Vectors.dense(10, 590, 190,
700) and get class ?

We try play with this:

val df = spark.createDataFrame(Array((10, 590, 190, 700)))
val pr_class = model.transform(df) 

but get error.

Thank you.






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