Scala GaussianMixtureModel类代码示例

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本文整理汇总了Scala中org.apache.spark.ml.clustering.GaussianMixtureModel类的典型用法代码示例。如果您正苦于以下问题：Scala GaussianMixtureModel类的具体用法？Scala GaussianMixtureModel怎么用？Scala GaussianMixtureModel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GaussianMixtureModel类的2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: LocalGaussianMixtureModel

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

import io.hydrosphere.spark_ml_serving._
import org.apache.spark.ml.clustering.GaussianMixtureModel
import org.apache.spark.ml.linalg.{Matrix, Vector}
import org.apache.spark.ml.stat.distribution.MultivariateGaussian

class LocalGaussianMixtureModel(override val sparkTransformer: GaussianMixtureModel) extends LocalTransformer[GaussianMixtureModel] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getFeaturesCol) match {
      case Some(column) =>
        val predictMethod = classOf[GaussianMixtureModel].getMethod("predict", classOf[Vector])
        predictMethod.setAccessible(true)
        val newColumn = LocalDataColumn(sparkTransformer.getPredictionCol, column.data map { feature =>
          predictMethod.invoke(sparkTransformer, feature.asInstanceOf[Vector]).asInstanceOf[Int]
        })
        localData.withColumn(newColumn)
      case None => localData
    }
  }
}

object LocalGaussianMixtureModel extends LocalModel[GaussianMixtureModel] {
  override def load(metadata: Metadata, data: Map[String, Any]): GaussianMixtureModel = {
    val weights = data("weights").asInstanceOf[List[Double]].toArray
    val mus = data("mus").asInstanceOf[List[Vector]].toArray
    val sigmas = data("sigmas").asInstanceOf[List[Matrix]].toArray
    val gaussians = mus zip sigmas map {
      case (mu, sigma) => new MultivariateGaussian(mu, sigma)
    }

    val constructor = classOf[GaussianMixtureModel].getDeclaredConstructor(
        classOf[String],
        classOf[Array[Double]],
        classOf[Array[MultivariateGaussian]]
    )
    constructor.setAccessible(true)
    var inst = constructor.newInstance(metadata.uid, weights, gaussians)
    inst = inst.set(inst.probabilityCol, metadata.paramMap("probabilityCol").asInstanceOf[String])
    inst = inst.set(inst.featuresCol, metadata.paramMap("featuresCol").asInstanceOf[String])
    inst = inst.set(inst.predictionCol, metadata.paramMap("predictionCol").asInstanceOf[String])
    inst
  }


  override implicit def getTransformer(transformer: GaussianMixtureModel): LocalTransformer[GaussianMixtureModel] = new LocalGaussianMixtureModel(transformer)
}

开发者ID:Hydrospheredata，项目名称:spark-ml-serving，代码行数:48，代码来源:LocalGaussianMixtureModel.scala

示例2: LocalGaussianMixtureModel

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

import io.hydrosphere.mist.api.ml._
import org.apache.spark.ml.clustering.GaussianMixtureModel
import org.apache.spark.ml.linalg.{Matrix, Vector}
import org.apache.spark.ml.stat.distribution.MultivariateGaussian

class LocalGaussianMixtureModel(override val sparkTransformer: GaussianMixtureModel) extends LocalTransformer[GaussianMixtureModel] {
  override def transform(localData: LocalData): LocalData = {
    localData.column(sparkTransformer.getFeaturesCol) match {
      case Some(column) =>
        val predictMethod = classOf[GaussianMixtureModel].getMethod("predict", classOf[Vector])
        predictMethod.setAccessible(true)
        val newColumn = LocalDataColumn(sparkTransformer.getPredictionCol, column.data map { feature =>
          predictMethod.invoke(sparkTransformer, feature.asInstanceOf[Vector]).asInstanceOf[Int]
        })
        localData.withColumn(newColumn)
      case None => localData
    }
  }
}

object LocalGaussianMixtureModel extends LocalModel[GaussianMixtureModel] {
  override def load(metadata: Metadata, data: Map[String, Any]): GaussianMixtureModel = {
    val weights = data("weights").asInstanceOf[List[Double]].toArray
    val mus = data("mus").asInstanceOf[List[Vector]].toArray
    val sigmas = data("sigmas").asInstanceOf[List[Matrix]].toArray
    val gaussians = mus zip sigmas map {
      case (mu, sigma) => new MultivariateGaussian(mu, sigma)
    }

    val constructor = classOf[GaussianMixtureModel].getDeclaredConstructor(
        classOf[String],
        classOf[Array[Double]],
        classOf[Array[MultivariateGaussian]]
    )
    constructor.setAccessible(true)
    var inst = constructor.newInstance(metadata.uid, weights, gaussians)
    inst = inst.set(inst.probabilityCol, metadata.paramMap("probabilityCol").asInstanceOf[String])
    inst = inst.set(inst.featuresCol, metadata.paramMap("featuresCol").asInstanceOf[String])
    inst = inst.set(inst.predictionCol, metadata.paramMap("predictionCol").asInstanceOf[String])
    inst
  }


  override implicit def getTransformer(transformer: GaussianMixtureModel): LocalTransformer[GaussianMixtureModel] = new LocalGaussianMixtureModel(transformer)
}

开发者ID:Hydrospheredata，项目名称:mist，代码行数:48，代码来源:LocalGaussianMixtureModel.scala

注：本文中的org.apache.spark.ml.clustering.GaussianMixtureModel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。