How to transform the dataframe into label feature vector?

Question

I am running a logistic regression modl in scala and I have a data frame like below:

df

+-----------+------------+
|x          |y           |
+----------         


        

Answer 1

Given the dataframe as

+---+---+
|x  |y  |
+---+---+
|0  |0  |
|0  |33 |
|0  |58 |
|0  |96 |
|0  |1  |
|1  |21 |
|0  |10 |
|0  |65 |
|1  |7  |
|1  |28 |
+---+---+

And doing as below

val assembler =  new VectorAssembler()
  .setInputCols(Array("x", "y"))
  .setOutputCol("features")

  val output = assembler.transform(df).select($"x".cast(DoubleType).as("label"), $"features")
output.show(false)

Would give you result as

+-----+----------+
|label|features  |
+-----+----------+
|0.0  |(2,[],[]) |
|0.0  |[0.0,33.0]|
|0.0  |[0.0,58.0]|
|0.0  |[0.0,96.0]|
|0.0  |[0.0,1.0] |
|1.0  |[1.0,21.0]|
|0.0  |[0.0,10.0]|
|0.0  |[0.0,65.0]|
|1.0  |[1.0,7.0] |
|1.0  |[1.0,28.0]|
+-----+----------+

Now using LogisticRegression would be easy

val lr = new LogisticRegression()
  .setMaxIter(10)
  .setRegParam(0.3)
  .setElasticNetParam(0.8)

val lrModel = lr.fit(output)
println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")

You will have output as

Coefficients: [1.5672602877378823,0.0] Intercept: -1.4055020984891717