keystoneml.nodes.learning

PerClassWeightedLeastSquaresEstimator

object PerClassWeightedLeastSquaresEstimator extends Logging with Serializable

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  1. PerClassWeightedLeastSquaresEstimator
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  8. def computeJointFeatureMean(features: RDD[DenseVector[Double]], labels: RDD[DenseVector[Double]], popFeatureMean: DenseVector[Double], mixtureWeight: Double, numExamples: Long, numFeatures: Int, numClasses: Int): (RDD[(Int, DenseVector[Double])], Array[Int])

  9. def computeJointLabelMean(classCounts: Array[Int], mixtureWeight: Double, numExamples: Long): DenseVector[Double]

  10. def computeWeights(labels: RDD[DenseVector[Double]], numExamples: Long, mixtureWeight: Double, classCounts: Array[Int]): RDD[DenseVector[Double]]

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  32. def toString(): String

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  33. def trainSingleClassWeightedLS(blockSize: Int, numBlocks: Int, numIter: Int, lambda: Double, numFeatures: Int, trainingFeatureBlocks: Seq[RDD[DenseVector[Double]]], classLabelsZm: RDD[Double], classWeights: RDD[Double], classMean: DenseVector[Double]): Seq[DenseVector[Double]]

  34. def trainWithL2(trainingFeatures: RDD[DenseVector[Double]], trainingLabels: RDD[DenseVector[Double]], blockSize: Int, numIter: Int, lambda: Double, mixtureWeight: Double, numFeaturesOpt: Option[Int]): BlockLinearMapper

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