All Classes and Interfaces

Class	Description
AdaDelta	An implementation of the AdaDelta gradient optimiser.
AdaGrad	An implementation of the AdaGrad gradient optimiser.
AdaGradRDA	An implementation of the AdaGrad gradient optimiser with regularized dual averaging.
Adam	An implementation of the Adam gradient optimiser.
CosineDistance	Cosine similarity used as a distance measure.
DenseMatrix	A dense matrix, backed by a primitive array.
DenseMatrix.CholeskyFactorization	The output of a successful Cholesky factorization.
DenseMatrix.EigenDecomposition	The output of a successful eigen decomposition.
DenseMatrix.LUFactorization	The output of a successful LU factorization.
DenseSparseMatrix	A matrix which is dense in the first dimension and sparse in the second.
DenseVector	A dense vector, backed by a double array.
Distance	Interface for distance functions.
DistanceType	The built-in distance functions.
ExpNormalizer	Normalizes the exponential values of the input array.
FeedForwardParameters	A Parameters for models which make a single prediction like logistic regressions and neural networks.
GradientOptimiserOptions	CLI options for configuring a gradient optimiser.
GradientOptimiserOptions.StochasticGradientOptimiserType	Type of the gradient optimisers available in CLIs.
HeapMerger	Merges each SparseVector separately using a PriorityQueue as a heap.
KDTree	A k-d tree nearest neighbour query implementation.
KDTreeFactory	A factory which creates k-d tree nearest neighbour query objects.
Kernel	An interface for a Mercer kernel function.
L1Distance	L1 (or Manhattan) distance.
L2Distance	L2 (or Euclidean) distance.
Linear	A linear kernel, u.dot(v).
LinearParameters	A Parameters for producing linear models.
Matrix	Interface for 2 dimensional Tensors.
Matrix.Factorization	Interface for matrix factorizations.
MatrixHeapMerger	Merges each DenseSparseMatrix using a PriorityQueue as a heap on the MatrixIterator.
MatrixIterator	A Comparable Iterator over MatrixTuples.
MatrixTuple	A mutable tuple used to avoid allocation when iterating a matrix.
Merger	An interface for merging an array of DenseSparseMatrix into a single DenseSparseMatrix.
MultivariateNormalDistribution	A class for sampling from multivariate normal distributions.
NeighboursBruteForce	A brute-force nearest neighbour query implementation.
NeighboursBruteForceFactory	A factory which creates brute-force nearest neighbour query objects.
NeighboursQuery	An interface for nearest neighbour query objects.
NeighboursQueryFactory	An interface for factories which create nearest neighbour query objects.
NeighboursQueryFactoryType	These are the supported neighbour query implementations.
NoopNormalizer	NoopNormalizer returns a copy in NoopNormalizer.normalize(double[]) and is a no-op in place.
Normalizer	Normalizes, but first subtracts the minimum value (to ensure positivity).
ONNXMathUtils	Tribuo Math specific helper functions for building ONNX protos.
ParameterAveraging	Averages the parameters across a gradient run.
Parameters	An interface to a Tensor[] array which accepts updates to the parameters.
Pegasos	An implementation of the Pegasos gradient optimiser used primarily for solving the SVM problem.
Polynomial	A polynomial kernel, (gamma*u.dot(v) + intercept)^degree.
RBF	A Radial Basis Function (RBF) kernel, exp(-gamma*|u-v|^2).
RMSProp	An implementation of the RMSProp gradient optimiser.
SGD	An implementation of single learning rate SGD and optionally momentum.
SGD.Momentum	Momentum types.
SGDVector	Interface for 1 dimensional Tensors.
ShrinkingMatrix	A subclass of DenseMatrix which shrinks the value every time a new value is added.
ShrinkingTensor	An interface which tags a Tensor with a convertToDense method.
ShrinkingVector	A subclass of DenseVector which shrinks the value every time a new value is added.
Sigmoid	A sigmoid kernel, tanh(gamma*u.dot(v) + intercept).
SigmoidNormalizer	Normalizes the input by applying a logistic sigmoid to each element.
SparseVector	A sparse vector.
StochasticGradientOptimiser	Interface for gradient based optimisation methods.
Tensor	An interface for Tensors, currently Vectors and Matrices.
VectorIterator	A Comparable Iterator over VectorTuples.
VectorNormalizer	A functional interface that generates a normalized version of a double array.
VectorTuple	A mutable tuple used to avoid allocation when iterating a vector.