从FlinkML多元线性回归中提取权重

Question

我正在运行Flink (0.10-SNAPSHOT)的示例多元线性回归。我不知道如何提取权重(例如斜率和截距，beta0-beta1，你想叫他们什么)。我对Scala不是很熟悉，这可能是我一半的问题。

感谢任何人给予的任何帮助。

object Job {
 def main(args: Array[String]) {
    // set up the execution environment
    val env = ExecutionEnvironment.getExecutionEnvironment
    val survival = env.readCsvFile[(String, String, String, String)]("/home/danger/IdeaProjects/quickstart/docs/haberman.data")
    val survivalLV = survival
      .map{tuple =>
      val list = tuple.productIterator.toList
      val numList = list.map(_.asInstanceOf[String].toDouble)
      LabeledVector(numList(3), DenseVector(numList.take(3).toArray))
    }
    val mlr = MultipleLinearRegression()
      .setStepsize(1.0)
      .setIterations(100)
      .setConvergenceThreshold(0.001)
    mlr.fit(survivalLV) 
    println(mlr.toString())     // This doesn't do anything productive...
    println(mlr.weightsOption)  // Neither does this.
  }
}

Answer 1

问题是您只构造了Flink作业(DAG)，它将计算权重，但尚未执行。触发执行的最简单方法是使用collect方法，该方法将检索DataSet的结果返回给您的客户端。

mlr.fit(survivalLV)
val weights = mlr.weightsOption match {
  case Some(weights) => weights.collect()
  case None => throw new Exception("Could not calculate the weights.")
}
println(weights)