Scala DCT类代码示例

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本文整理汇总了Scala中org.apache.spark.ml.feature.DCT类的典型用法代码示例。如果您正苦于以下问题：Scala DCT类的具体用法？Scala DCT怎么用？Scala DCT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DCT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: LocalDCT

//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.DCT
import org.apache.spark.ml.linalg.{Vector, Vectors}

class LocalDCT(override val sparkTransformer: DCT) extends LocalTransformer[DCT] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getInputCol) match {
      case Some(column) =>
        val method = classOf[DCT].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 LocalDCT extends LocalModel[DCT] {
  override def load(metadata: Metadata, data: Map[String, Any]): DCT = {
    new DCT(metadata.uid)
      .setInputCol(metadata.paramMap("inputCol").asInstanceOf[String])
      .setOutputCol(metadata.paramMap("outputCol").asInstanceOf[String])
      .setInverse(metadata.paramMap("inverse").asInstanceOf[Boolean])
  }

  override implicit def getTransformer(transformer: DCT): LocalTransformer[DCT] = new LocalDCT(transformer)
}

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

示例2: LocalDCT

//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.DCT
import org.apache.spark.ml.linalg.{Vector, Vectors}

class LocalDCT(override val sparkTransformer: DCT) extends LocalTransformer[DCT] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getInputCol) match {
      case Some(column) =>
        val method = classOf[DCT].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 LocalDCT extends LocalModel[DCT] {
  override def load(metadata: Metadata, data: Map[String, Any]): DCT = {
    new DCT(metadata.uid)
      .setInputCol(metadata.paramMap("inputCol").asInstanceOf[String])
      .setOutputCol(metadata.paramMap("outputCol").asInstanceOf[String])
      .setInverse(metadata.paramMap("inverse").asInstanceOf[Boolean])
  }

  override implicit def getTransformer(transformer: DCT): LocalTransformer[DCT] = new LocalDCT(transformer)
}

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

示例3: DCTJob

//设置package包名称以及导入依赖的类
import BinarizerJob.context
import io.hydrosphere.mist.api._
import io.hydrosphere.mist.api.ml._
import org.apache.spark.ml.Pipeline
import org.apache.spark.ml.feature.DCT
import org.apache.spark.ml.linalg.{Vector => LVector, Vectors => LVectors}
import org.apache.spark.sql.SparkSession

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

  def train(savePath: String): Map[String, Any] = {
    val data = Seq(
      LVectors.dense(0.0, 1.0, -2.0, 3.0),
      LVectors.dense(-1.0, 2.0, 4.0, -7.0),
      LVectors.dense(14.0, -2.0, -5.0, 1.0)
    )
    val df = session.createDataFrame(data.map(Tuple1.apply)).toDF("features")

    val dct = new DCT()
      .setInputCol("features")
      .setOutputCol("featuresDCT")
      .setInverse(false)

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

    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 response = result.select("category", "featuresDCT").toMapList.map(rowMap => {
      val mapped = rowMap("featuresDCT").asInstanceOf[LVector].toArray
      rowMap + ("featuresDCT" -> mapped)
    })

    Map("result" -> response)
  }
}

开发者ID:Hydrospheredata，项目名称:mist，代码行数:52，代码来源:DCTJob.scala

注：本文中的org.apache.spark.ml.feature.DCT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。