Scala PolynomialExpansion类代码示例

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本文整理汇总了Scala中org.apache.spark.ml.feature.PolynomialExpansion类的典型用法代码示例。如果您正苦于以下问题：Scala PolynomialExpansion类的具体用法？Scala PolynomialExpansion怎么用？Scala PolynomialExpansion使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。

在下文中一共展示了PolynomialExpansion类的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Scala代码示例。

示例1: LocalPolynomialExpansion

//设置package包名称以及导入依赖的类
package io.hydrosphere.spark_ml_serving.preprocessors

import io.hydrosphere.spark_ml_serving._
import org.apache.spark.ml.feature.PolynomialExpansion
import org.apache.spark.ml.linalg.{Vector, Vectors}

class LocalPolynomialExpansion(override val sparkTransformer: PolynomialExpansion) extends LocalTransformer[PolynomialExpansion] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getInputCol) match {
      case Some(column) =>
        val method = classOf[PolynomialExpansion].getMethod("createTransformFunc")
        val newData = column.data.map(r => {
          val row = r.asInstanceOf[List[Any]].map(_.toString.toDouble).toArray
          val vector: Vector = Vectors.dense(row)
          method.invoke(sparkTransformer).asInstanceOf[Vector => Vector](vector)
        })
        localData.withColumn(LocalDataColumn(sparkTransformer.getOutputCol, newData))
      case None => localData
    }
  }
}

object LocalPolynomialExpansion extends LocalModel[PolynomialExpansion] {
  override def load(metadata: Metadata, data: Map[String, Any]): PolynomialExpansion = {
    new PolynomialExpansion(metadata.uid)
      .setInputCol(metadata.paramMap("inputCol").asInstanceOf[String])
      .setOutputCol(metadata.paramMap("outputCol").asInstanceOf[String])
      .setDegree(metadata.paramMap("degree").asInstanceOf[Number].intValue())
  }

  override implicit def getTransformer(transformer: PolynomialExpansion): LocalTransformer[PolynomialExpansion] = new LocalPolynomialExpansion(transformer)
}

开发者ID:Hydrospheredata，项目名称:spark-ml-serving，代码行数:33，代码来源:LocalPolynomialExpansion.scala

示例2: LocalPolynomialExpansion

//设置package包名称以及导入依赖的类
package io.hydrosphere.mist.api.ml.preprocessors

import io.hydrosphere.mist.api.ml._
import org.apache.spark.ml.feature.PolynomialExpansion
import org.apache.spark.ml.linalg.{Vector, Vectors}

class LocalPolynomialExpansion(override val sparkTransformer: PolynomialExpansion) extends LocalTransformer[PolynomialExpansion] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getInputCol) match {
      case Some(column) =>
        val method = classOf[PolynomialExpansion].getMethod("createTransformFunc")
        val newData = column.data.map(r => {
          val row = r.asInstanceOf[List[Any]].map(_.toString.toDouble).toArray
          val vector: Vector = Vectors.dense(row)
          method.invoke(sparkTransformer).asInstanceOf[Vector => Vector](vector)
        })
        localData.withColumn(LocalDataColumn(sparkTransformer.getOutputCol, newData))
      case None => localData
    }
  }
}

object LocalPolynomialExpansion extends LocalModel[PolynomialExpansion] {
  override def load(metadata: Metadata, data: Map[String, Any]): PolynomialExpansion = {
    new PolynomialExpansion(metadata.uid)
      .setInputCol(metadata.paramMap("inputCol").asInstanceOf[String])
      .setOutputCol(metadata.paramMap("outputCol").asInstanceOf[String])
      .setDegree(metadata.paramMap("degree").asInstanceOf[Number].intValue())
  }

  override implicit def getTransformer(transformer: PolynomialExpansion): LocalTransformer[PolynomialExpansion] = new LocalPolynomialExpansion(transformer)
}

开发者ID:Hydrospheredata，项目名称:mist，代码行数:33，代码来源:LocalPolynomialExpansion.scala

示例3: PolynomialExpansionJob

//设置package包名称以及导入依赖的类
import io.hydrosphere.mist.api._
import io.hydrosphere.mist.api.ml._
import org.apache.spark.ml.Pipeline
import org.apache.spark.ml.feature.PolynomialExpansion
import org.apache.spark.ml.linalg.{DenseVector, Vectors}
import org.apache.spark.sql.SparkSession

object PolynomialExpansionJob extends MLMistJob {
  def session: SparkSession = SparkSession
    .builder()
    .appName(context.appName)
    .config(context.getConf)
    .getOrCreate()

  def train(savePath: String): Map[String, Any] = {
    val data = Array(
      Vectors.dense(2.0, 1.0),
      Vectors.dense(0.0, 0.0),
      Vectors.dense(3.0, -1.0)
    )
    val df = session.createDataFrame(data.map(Tuple1.apply)).toDF("features")

    val polyExpansion = new PolynomialExpansion()
      .setInputCol("features")
      .setOutputCol("polyFeatures")
      .setDegree(3)

    val pipeline = new Pipeline().setStages(Array(polyExpansion))

    val model = pipeline.fit(df)

    model.write.overwrite().save(savePath)
    Map.empty[String, Any]
  }

  def serve(modelPath: String, features: List[List[Double]]): Map[String, Any] = {
    import LocalPipelineModel._

    val pipeline = PipelineLoader.load(modelPath)
    val data = LocalData(LocalDataColumn("features", features))

    val result = pipeline.transform(data)
    val column = result.column("polyFeatures").map(_.asInstanceOf[LocalDataColumn[DenseVector]])
    val response = column.map(c => c.data.map(_.toArray))

    Map("result" -> response)
  }
}

开发者ID:Hydrospheredata，项目名称:mist，代码行数:49，代码来源:PolynomialExpansionJob.scala

注：本文中的org.apache.spark.ml.feature.PolynomialExpansion类示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。