Flink多元线性回归：是否具有预测？

Question

I've a multiple regression model trained and now I want to use it to predict.

Reading the documents I understand that the input is a labeled vector and the output is a Dataset with tuple [ InputValue, PredictValue ], right?

I create my labeled Vector:

val mapped = data.map {x => new org.apache.flink.ml.common.LabeledVector (x._4, org.apache.flink.ml.math.DenseVector(x._1,x._2,x._3)) }

//Print
mapped: org.apache.flink.api.scala.DataSet[org.apache.flink.ml.common.LabeledVector] = org.apache.flink.api.scala.DataSet@7d4fefdc
LabeledVector(6.7, DenseVector(33.0, -52.26, 28.3))
LabeledVector(5.8, DenseVector(36.0, 45.53, 150.93))
.....

And with my model created and trained I predict:

// Calculate the predictions for the test data
val predictions = mlr.predict(mapped)

I got this ERROR :

java.lang.RuntimeException: There is no PredictOperation defined for org.apache.flink.ml.regression.MultipleLinearRegression which takes a DataSet[org.apache.flink.ml.common.LabeledVector] as input.

But you can see here that the official documentation say that it exits.

Thanks for your help! :)

Answer 1

The prediction of LabeledVectors has been removed with this commit . Unfortunately, the Flink documentation has not been updated. I've created an issue to update the documentation.

If you want to predict LabeledVectors , then you have to write your own PredictOperation which supports the respective types.