DIMENSION
MLUtils
Default
LearningRateMethod
Degree
PolynomialFeatures
DenseMatrix
math
DenseVector
math
DistanceMetric
distances KNN
DistributedMatrix
distributed
DistributedRowMatrix
distributed
data
DenseMatrix DenseVector SparseMatrix SparseVector DistributedRowMatrix BreezeLabeledVector
decay
InvScaling Xu
defaultEvaluateDataSetOperation
Predictor
defaultPredictDataSetOperation
Predictor
defaultTransformDataSetOperation
Transformer
defaultValue
Blocks Iterations LocalIterations OutputDecisionFunction Regularization Seed Stepsize ThresholdValue Parameter Blocks DistanceMetric K SizeHint UseQuadTree ConvergenceThreshold Iterations LearningRate LearningRateMethodValue LossFunction RegularizationConstant RegularizationPenaltyValue ErrorTolerance MaxIterations Perplexity Max Min Degree Mean Std Blocks Iterations Lambda NumFactors Seed TemporaryPath ConvergenceThreshold Iterations LearningRateMethodValue Stepsize
denseVectorBuilder
VectorBuilder
denseVectorConverter
DenseVector
derivative
HingeLoss LogisticLoss PartialLossFunction SquaredLoss
distance
ChebyshevDistanceMetric CosineDistanceMetric DistanceMetric EuclideanDistanceMetric ManhattanDistanceMetric MinkowskiDistanceMetric SquaredEuclideanDistanceMetric TanimotoDistanceMetric
distances
metrics
distributed
math
dot
BLAS DenseVector SparseVector Vector