ReWeightedLeastSquaresSolver

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30. def trainWithL2(blockSize: Int, numBlocks: Int, numIter: Int, lambda: Double, numFeatures: Int, numClasses: Int, trainingFeatureBlocks: Seq[RDD[DenseVector[Double]]], labelsZm: RDD[DenseVector[Double]], weights: RDD[Double], featureMean: DenseVector[Double]): (Seq[DenseMatrix[Double]], RDD[DenseMatrix[Double]])

    Use BCD to solve W = (X.

    Use BCD to solve W = (X.t * (diag(B) * X) + \lambda * I) \ X.t * (B .* Y)

    blockSize

    blockSize to use for Block Coordinate Descent

    numBlocks

    number of blocks in the input

    numIter

    number of iterations of BCD to run

    lambda

    L2 regularization parameter

    numFeatures

    number of features in the input (columns in X)

    numClasses

    number of classes (columns in Y)

    trainingFeatureBlocks

    blocks of input features

    labelsZm

    zero-mean'd labels matrix

    weights

    diagonal values for the weights matrix

    featureMean

    mean to be subtracted from X before the solve

31. final def wait(): Unit

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