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