Index (Math 4.3.2 API)

A B C D E F G H I J K L M N O P Q R S T U V
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

AdaDelta - Class in org.tribuo.math.optimisers: An implementation of the AdaDelta gradient optimiser.
AdaDelta() - Constructor for class org.tribuo.math.optimisers.AdaDelta: Sets rho to 0.95 and epsilon to 1e-6.
AdaDelta(double) - Constructor for class org.tribuo.math.optimisers.AdaDelta: Keeps rho at 0.95, passes through epsilon.
AdaDelta(double, double) - Constructor for class org.tribuo.math.optimisers.AdaDelta: It's recommended to keep rho at 0.95.
ADADELTA - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The AdaDelta optimiser.
AdaGrad - Class in org.tribuo.math.optimisers: An implementation of the AdaGrad gradient optimiser.
AdaGrad(double) - Constructor for class org.tribuo.math.optimisers.AdaGrad: Creates an AdaGrad optimiser using the specified initial learning rate.
AdaGrad(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGrad: Creates an AdaGrad optimiser using the specified learning rate and epsilon.
AdaGrad(double, double, double) - Constructor for class org.tribuo.math.optimisers.AdaGrad: Creates an AdaGrad optimiser using the specified learning rate, epsilon and initial accumulator value.
ADAGRAD - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The AdaGrad optimiser.
AdaGradRDA - Class in org.tribuo.math.optimisers: An implementation of the AdaGrad gradient optimiser with regularized dual averaging.
AdaGradRDA(double, double) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA: Creates an AdaGradRDA optimiser with the specified parameter values.
AdaGradRDA(double, double, double, double, int) - Constructor for class org.tribuo.math.optimisers.AdaGradRDA: Creates an AdaGradRDA optimiser with the specified parameter values.
ADAGRADRDA - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The AdaGrad Regularised Dual Averaging optimiser.
Adam - Class in org.tribuo.math.optimisers: An implementation of the Adam gradient optimiser.
Adam() - Constructor for class org.tribuo.math.optimisers.Adam: Sets initialLearningRate to 0.001, betaOne to 0.9, betaTwo to 0.999, epsilon to 1e-6.
Adam(double, double) - Constructor for class org.tribuo.math.optimisers.Adam: Sets betaOne to 0.9 and betaTwo to 0.999
Adam(double, double, double, double) - Constructor for class org.tribuo.math.optimisers.Adam: It's highly recommended not to modify these parameters, use one of the other constructors.
ADAM - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The Adam optimiser.
add(int, double) - Method in class org.tribuo.math.la.DenseVector
add(int, double) - Method in interface org.tribuo.math.la.SGDVector: Adds value to the element at index.
add(int, double) - Method in class org.tribuo.math.la.SparseVector
add(int, int, double) - Method in class org.tribuo.math.la.DenseMatrix
add(int, int, double) - Method in class org.tribuo.math.la.DenseSparseMatrix
add(int, int, double) - Method in interface org.tribuo.math.la.Matrix: Adds the argument value to the value at the supplied index.
add(DenseMatrix) - Method in class org.tribuo.math.la.DenseMatrix: Adds other to this matrix, producing a new DenseMatrix.
add(SGDVector) - Method in class org.tribuo.math.la.DenseVector: Adds other to this vector, producing a new DenseVector.
add(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Adds other to this vector, producing a new SGDVector.
add(SGDVector) - Method in class org.tribuo.math.la.SparseVector: Adds other to this vector, producing a new SGDVector.
addAcrossDim1(int[], double) - Method in class org.tribuo.math.la.DenseMatrix: Adds the specified value to the specified elements across dimension 1.
addAcrossDim2(int[], double) - Method in class org.tribuo.math.la.DenseMatrix: Adds the specified value to the specified elements across dimension 2.
approximateParentNode(SGDVector) - Method in class org.tribuo.math.neighbour.kdtree.KDTree: This makes a fast approximation of the provided point's parent node, if it were being inserted into the tree.
argmax() - Method in class org.tribuo.math.la.DenseVector: Gets the index of the maximum element.

B

broadcastIntersectAndAddInPlace(SGDVector, boolean) - Method in class org.tribuo.math.la.DenseMatrix: Broadcasts the input vector and adds it to each row/column of the matrix.
BRUTE_FORCE - Enum constant in enum org.tribuo.math.neighbour.NeighboursQueryFactoryType: A factory which emits nearest neighbour query objects using a brute-force search.

C

choleskyFactorization() - Method in class org.tribuo.math.la.DenseMatrix: Computes the Cholesky factorization of a positive definite matrix.
columnSum() - Method in class org.tribuo.math.la.DenseMatrix: Returns a dense vector containing each column sum.
columnSum(int) - Method in class org.tribuo.math.la.DenseMatrix: Calculates the sum of the specified column.
compareTo(MatrixIterator) - Method in interface org.tribuo.math.la.MatrixIterator
compareTo(VectorIterator) - Method in interface org.tribuo.math.la.VectorIterator
computeDistance(SGDVector, SGDVector) - Method in class org.tribuo.math.distance.CosineDistance
computeDistance(SGDVector, SGDVector) - Method in interface org.tribuo.math.distance.Distance: Computes the distance between the two vectors.
computeDistance(SGDVector, SGDVector) - Method in enum org.tribuo.math.distance.DistanceType: Calculates the distance between two vectors.
computeDistance(SGDVector, SGDVector) - Method in class org.tribuo.math.distance.L1Distance
computeDistance(SGDVector, SGDVector) - Method in class org.tribuo.math.distance.L2Distance
CONSTANTSGD - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: SGD with a constant learning rate.
convertToDense() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
convertToDense() - Method in interface org.tribuo.math.optimisers.util.ShrinkingTensor: Converts the tensor into a dense tensor.
convertToDense() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
copy() - Method in interface org.tribuo.math.FeedForwardParameters: Returns a copy of the parameters.
copy() - Method in class org.tribuo.math.la.DenseMatrix: Copies the matrix.
copy() - Method in class org.tribuo.math.la.DenseSparseMatrix
copy() - Method in class org.tribuo.math.la.DenseVector
copy() - Method in interface org.tribuo.math.la.Matrix: Copies the matrix.
copy() - Method in interface org.tribuo.math.la.SGDVector: Returns a deep copy of this vector.
copy() - Method in class org.tribuo.math.la.SparseVector
copy() - Method in interface org.tribuo.math.la.Tensor: Returns a copy of this Tensor.
copy() - Method in class org.tribuo.math.LinearParameters
copy() - Method in class org.tribuo.math.optimisers.AdaDelta
copy() - Method in class org.tribuo.math.optimisers.AdaGrad
copy() - Method in class org.tribuo.math.optimisers.AdaGradRDA
copy() - Method in class org.tribuo.math.optimisers.Adam
copy() - Method in class org.tribuo.math.optimisers.ParameterAveraging
copy() - Method in class org.tribuo.math.optimisers.Pegasos
copy() - Method in class org.tribuo.math.optimisers.RMSProp
copy() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
copy() - Method in interface org.tribuo.math.StochasticGradientOptimiser: Copies a gradient optimiser with it's configuration.
COSINE - Enum constant in enum org.tribuo.math.distance.DistanceType: Cosine similarity used as a distance measure.
cosineDistance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Calculates the cosine distance of two vectors.
CosineDistance - Class in org.tribuo.math.distance: Cosine similarity used as a distance measure.
CosineDistance() - Constructor for class org.tribuo.math.distance.CosineDistance: Constructs a Cosine distance function.
cosineSimilarity(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Calculates the cosine similarity of two vectors.
createDenseMatrix(double[][]) - Static method in class org.tribuo.math.la.DenseMatrix: Defensively copies the values before construction.
createDenseMatrix(SGDVector[]) - Static method in class org.tribuo.math.la.DenseMatrix: Constructs a new DenseMatrix copying the values from the supplied vectors.
createDenseVector(double[]) - Static method in class org.tribuo.math.la.DenseVector: Defensively copies the values before construction.
createDenseVector(Example<T>, ImmutableFeatureMap, boolean) - Static method in class org.tribuo.math.la.DenseVector: Builds a DenseVector from an Example.
createDiagonal(SGDVector) - Static method in class org.tribuo.math.la.DenseSparseMatrix: Creates a diagonal matrix using the supplied values.
createFromSparseVectors(SparseVector[]) - Static method in class org.tribuo.math.la.DenseSparseMatrix: Defensively copies the values.
createIdentity(int) - Static method in class org.tribuo.math.la.DenseMatrix: Creates an identity matrix of the specified size.
createIdentity(int) - Static method in class org.tribuo.math.la.DenseSparseMatrix: Creates an identity matrix of the specified size.
createNeighboursQuery(SGDVector[]) - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory: Constructs a brute-force nearest neighbor query object using the supplied array of SGDVector.
createNeighboursQuery(SGDVector[]) - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory: Constructs a k-d tree nearest neighbor query object using the supplied array of SGDVector.
createNeighboursQuery(SGDVector[]) - Method in interface org.tribuo.math.neighbour.NeighboursQueryFactory: Constructs a nearest neighbour query object using the supplied array of SGDVector.
createSparseVector(int, int[], double[]) - Static method in class org.tribuo.math.la.SparseVector: Defensively copies the input, and checks that the indices are sorted.
createSparseVector(int, Map<Integer, Double>) - Static method in class org.tribuo.math.la.SparseVector: Builds a SparseVector from a map.
createSparseVector(Example<T>, ImmutableFeatureMap, boolean) - Static method in class org.tribuo.math.la.SparseVector: Builds a SparseVector from an Example.
CURRENT_VERSION - Static variable in class org.tribuo.math.distance.CosineDistance: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.distance.L1Distance: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.distance.L2Distance: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.kernel.Linear: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.kernel.Polynomial: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.kernel.RBF: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.kernel.Sigmoid: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.la.DenseMatrix: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.la.DenseSparseMatrix: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.la.DenseVector: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.la.SparseVector: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.LinearParameters: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.neighbour.kdtree.KDTreeFactory: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.ExpNormalizer: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.HeapMerger: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.MatrixHeapMerger: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.NoopNormalizer: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.Normalizer: Protobuf serialization version.
CURRENT_VERSION - Static variable in class org.tribuo.math.util.SigmoidNormalizer: Protobuf serialization version.

D

DELTA - Static variable in class org.tribuo.math.la.VectorTuple: The tolerance for equality in value comparisons.
DenseMatrix - Class in org.tribuo.math.la: A dense matrix, backed by a primitive array.
DenseMatrix(int, int) - Constructor for class org.tribuo.math.la.DenseMatrix: Creates a dense matrix full of zeros.
DenseMatrix(DenseMatrix) - Constructor for class org.tribuo.math.la.DenseMatrix: Copies the supplied matrix.
DenseMatrix(Matrix) - Constructor for class org.tribuo.math.la.DenseMatrix: Copies the supplied matrix, densifying it if it's sparse.
DenseMatrix.CholeskyFactorization - Class in org.tribuo.math.la: The output of a successful Cholesky factorization.
DenseMatrix.EigenDecomposition - Class in org.tribuo.math.la: The output of a successful eigen decomposition.
DenseMatrix.LUFactorization - Class in org.tribuo.math.la: The output of a successful LU factorization.
DenseSparseMatrix - Class in org.tribuo.math.la: A matrix which is dense in the first dimension and sparse in the second.
DenseSparseMatrix(int, int) - Constructor for class org.tribuo.math.la.DenseSparseMatrix: Creates a DenseSparseMatrix with no values or indices.
DenseSparseMatrix(List<SparseVector>) - Constructor for class org.tribuo.math.la.DenseSparseMatrix: Constructs a DenseSparseMatrix out of the supplied sparse vector list.
DenseSparseMatrix(DenseSparseMatrix) - Constructor for class org.tribuo.math.la.DenseSparseMatrix: Creates a new DenseSparseMatrix by deep copying the supplied DenseSparseMatrix.
DenseVector - Class in org.tribuo.math.la: A dense vector, backed by a double array.
DenseVector(double[]) - Constructor for class org.tribuo.math.la.DenseVector: Does not defensively copy the input, used internally.
DenseVector(int) - Constructor for class org.tribuo.math.la.DenseVector: Creates an empty dense vector of the specified size.
DenseVector(int, double) - Constructor for class org.tribuo.math.la.DenseVector: Creates a dense vector of the specified size where each element is initialised to the specified value.
DenseVector(DenseVector) - Constructor for class org.tribuo.math.la.DenseVector: Copy constructor.
densify() - Method in class org.tribuo.math.la.SparseVector: Returns a dense vector copying this sparse vector.
deserialize(KernelProto) - Static method in interface org.tribuo.math.kernel.Kernel: Deserializes the kernel from the supplied protobuf.
deserialize(NeighbourFactoryProto) - Static method in interface org.tribuo.math.neighbour.NeighboursQueryFactory: Deserialization helper for NeighboursQueryFactories.
deserialize(NormalizerProto) - Static method in interface org.tribuo.math.util.VectorNormalizer: Deserializes the vector normalizer from the supplied protobuf.
deserialize(ParametersProto) - Static method in interface org.tribuo.math.Parameters: Deserializes the parameters from the supplied protobuf.
deserialize(TensorProto) - Static method in interface org.tribuo.math.la.Tensor: Deserialize a tensor proto into a Tensor.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.distance.CosineDistance: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.distance.L1Distance: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.distance.L2Distance: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.kernel.Linear: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.kernel.Polynomial: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.kernel.RBF: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.kernel.Sigmoid: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.la.DenseMatrix: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.la.DenseSparseMatrix: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.la.DenseVector: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.la.SparseVector: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.LinearParameters: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.optimisers.util.ShrinkingMatrix: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.optimisers.util.ShrinkingVector: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.ExpNormalizer: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.HeapMerger: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.MatrixHeapMerger: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.NoopNormalizer: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.Normalizer: Deserialization factory.
deserializeFromProto(int, String, Any) - Static method in class org.tribuo.math.util.SigmoidNormalizer: Deserialization factory.
determinant() - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization: Compute the matrix determinant of the factorized matrix.
determinant() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Computes the determinant of the matrix which was decomposed.
determinant() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: Compute the matrix determinant of the factorized matrix.
determinant() - Method in interface org.tribuo.math.la.Matrix.Factorization: Compute the matrix determinant of the factorized matrix.
diagonal() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: The diagonal vector of the tridiagonal form.
difference(SparseVector) - Method in class org.tribuo.math.la.SparseVector: Generates an array of the indices that are active in this vector but are not present in other.
dim1 - Variable in class org.tribuo.math.la.DenseMatrix: The number of rows.
dim1() - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization
dim1() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition
dim1() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization
dim1() - Method in interface org.tribuo.math.la.Matrix.Factorization: First dimension of the factorized matrix.
dim2 - Variable in class org.tribuo.math.la.DenseMatrix: The number of columns.
dim2() - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization
dim2() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition
dim2() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization
dim2() - Method in interface org.tribuo.math.la.Matrix.Factorization: Second dimension of the factorized matrix.
distance(SGDVector, DoubleUnaryOperator, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector: Computes the distance between this vector and the other vector.
Distance - Interface in org.tribuo.math.distance: Interface for distance functions.
DistanceType - Enum in org.tribuo.math.distance: The built-in distance functions.
dot(SGDVector) - Method in class org.tribuo.math.la.DenseVector
dot(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Calculates the dot product between this vector and other.
dot(SGDVector) - Method in class org.tribuo.math.la.SparseVector
dot(SGDVector) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector

E

eigenDecomposition() - Method in class org.tribuo.math.la.DenseMatrix: Eigen decomposition of a symmetric matrix.
eigenvalues() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: The vector of eigenvalues, in descending order.
eigenvectors() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: The eigenvectors for each eigenvalue, stored in the columns of the matrix.
elements - Variable in class org.tribuo.math.la.DenseVector: The value array.
epsilon - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Epsilon for AdaDelta, AdaGrad, AdaGradRDA, Adam.
equals(Object) - Method in class org.tribuo.math.distance.CosineDistance
equals(Object) - Method in class org.tribuo.math.distance.L1Distance
equals(Object) - Method in class org.tribuo.math.distance.L2Distance
equals(Object) - Method in class org.tribuo.math.kernel.Linear
equals(Object) - Method in class org.tribuo.math.kernel.Polynomial
equals(Object) - Method in class org.tribuo.math.kernel.RBF
equals(Object) - Method in class org.tribuo.math.kernel.Sigmoid
equals(Object) - Method in class org.tribuo.math.la.DenseMatrix
equals(Object) - Method in class org.tribuo.math.la.DenseSparseMatrix
equals(Object) - Method in class org.tribuo.math.la.DenseVector: Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
equals(Object) - Method in class org.tribuo.math.la.MatrixTuple
equals(Object) - Method in class org.tribuo.math.la.SparseVector: Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
equals(Object) - Method in class org.tribuo.math.la.VectorTuple
equals(Object) - Method in class org.tribuo.math.LinearParameters
equals(Object) - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory
equals(Object) - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory
equals(Object) - Method in class org.tribuo.math.util.ExpNormalizer
equals(Object) - Method in class org.tribuo.math.util.HeapMerger
equals(Object) - Method in class org.tribuo.math.util.MatrixHeapMerger
equals(Object) - Method in class org.tribuo.math.util.NoopNormalizer
equals(Object) - Method in class org.tribuo.math.util.Normalizer
equals(Object) - Method in class org.tribuo.math.util.SigmoidNormalizer
euclideanDistance(SGDVector) - Method in class org.tribuo.math.la.DenseVector: The l2 or euclidean distance between this vector and the other vector.
euclideanDistance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: The l2 or euclidean distance between this vector and the other vector.
euclideanDistance(SGDVector) - Method in class org.tribuo.math.la.SparseVector
expNormalize(double) - Method in class org.tribuo.math.la.DenseVector: An optimisation for the exponential normalizer when you already know the normalization constant.
ExpNormalizer - Class in org.tribuo.math.util: Normalizes the exponential values of the input array.
ExpNormalizer() - Constructor for class org.tribuo.math.util.ExpNormalizer: Constructs an ExpNormalizer.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.ExpNormalizer: Returns the ONNX softmax node over the 2nd dimension.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.NoopNormalizer: Returns its input.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.Normalizer: Applies ONNX ReduceMin, Sub, ReduceSum, and Div operations to input.
exportNormalizer(ONNXNode) - Method in class org.tribuo.math.util.SigmoidNormalizer: Returns the ONNX sigmoid node, operating independently over each element.
exportNormalizer(ONNXNode) - Method in interface org.tribuo.math.util.VectorNormalizer: Exports this normalizer to ONNX, returning the leaf of the appended graph and writing the nodes needed for normalization into the ONNXContext that input belongs to.

F

FACTORIZATION_TOLERANCE - Static variable in class org.tribuo.math.la.DenseMatrix: Tolerance for non-zero diagonal values in the factorizations.
FeedForwardParameters - Interface in org.tribuo.math: A Parameters for models which make a single prediction like logistic regressions and neural networks.
fill(double) - Method in class org.tribuo.math.la.DenseVector: Fills this DenseVector with value.
finalise() - Method in class org.tribuo.math.optimisers.AdaGradRDA
finalise() - Method in class org.tribuo.math.optimisers.ParameterAveraging: This sets the parameters to their average value.
finalise() - Method in class org.tribuo.math.optimisers.Pegasos
finalise() - Method in interface org.tribuo.math.StochasticGradientOptimiser: Finalises the gradient optimisation, setting the parameters to their correct values.
floatMatrix(ONNXContext, String, Matrix, boolean) - Static method in class org.tribuo.math.onnx.ONNXMathUtils: Builds a ONNXInitializer containing the Matrix.
floatVector(ONNXContext, String, SGDVector) - Static method in class org.tribuo.math.onnx.ONNXMathUtils: Builds a ONNXInitializer containing the SGDVector.
foreach(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector: Applies the function f to each element of this vector returning a new vector.
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in class org.tribuo.math.la.DenseVector
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in interface org.tribuo.math.la.SGDVector: Applies a ToDoubleBiFunction elementwise to this SGDVector.
foreachIndexedInPlace(ToDoubleBiFunction<Integer, Double>) - Method in class org.tribuo.math.la.SparseVector: Applies a ToDoubleBiFunction elementwise to this SGDVector.
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
foreachInPlace(DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector: Applies a DoubleUnaryOperator elementwise to this SGDVector.
foreachInPlace(DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor: Applies a DoubleUnaryOperator elementwise to this Tensor.

G

gatherAcrossDim1(int[]) - Method in class org.tribuo.math.la.DenseMatrix: Constructs a dense vector by gathering values across dimension 1.
gatherAcrossDim2(int[]) - Method in class org.tribuo.math.la.DenseMatrix: Constructs a dense vector by gathering values across dimension 2.
get() - Method in class org.tribuo.math.LinearParameters
get() - Method in interface org.tribuo.math.Parameters: Get a reference to the underlying Tensor array.
get(int) - Method in class org.tribuo.math.la.DenseVector
get(int) - Method in interface org.tribuo.math.la.SGDVector: Gets an element from this vector.
get(int) - Method in class org.tribuo.math.la.SparseVector
get(int) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
get(int, int) - Method in class org.tribuo.math.la.DenseMatrix
get(int, int) - Method in class org.tribuo.math.la.DenseSparseMatrix
get(int, int) - Method in interface org.tribuo.math.la.Matrix: Gets an element from this Matrix.
get(int, int) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
getColumn(int) - Method in class org.tribuo.math.la.DenseMatrix: Returns a copy of the specified column.
getColumn(int) - Method in class org.tribuo.math.la.DenseSparseMatrix: Gets a copy of the column.
getColumn(int) - Method in interface org.tribuo.math.la.Matrix: Returns a copy of the specified column.
getDimension1Size() - Method in class org.tribuo.math.la.DenseMatrix
getDimension1Size() - Method in class org.tribuo.math.la.DenseSparseMatrix
getDimension1Size() - Method in interface org.tribuo.math.la.Matrix: The size of the first dimension.
getDimension2Size() - Method in class org.tribuo.math.la.DenseMatrix
getDimension2Size() - Method in class org.tribuo.math.la.DenseSparseMatrix
getDimension2Size() - Method in interface org.tribuo.math.la.Matrix: The size of the second dimension.
getDistance() - Method in enum org.tribuo.math.distance.DistanceType: Gets the Distance object specified by this enum.
getDistance() - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory
getDistance() - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory
getDistance() - Method in interface org.tribuo.math.neighbour.NeighboursQueryFactory: Gets the Distance set on this object.
getEigenVector(int) - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Returns the dense vector representing the i'th eigenvector.
getEmptyCopy() - Method in class org.tribuo.math.LinearParameters: This returns a DenseMatrix the same size as the Parameters.
getEmptyCopy() - Method in interface org.tribuo.math.Parameters: Generates an empty copy of the underlying Tensor array.
getLinearDecaySGD(double) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a linearly decaying learning rate initialised to learningRate.
getLinearDecaySGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a linearly decaying learning rate initialised to learningRate, with momentum.
getNeighboursQueryFactory(NeighboursQueryFactoryType, Distance, int) - Static method in enum org.tribuo.math.neighbour.NeighboursQueryFactoryType: Returns the appropriate NeighboursQueryFactory implementation.
getNumThreads() - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory
getNumThreads() - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory
getNumThreads() - Method in interface org.tribuo.math.neighbour.NeighboursQueryFactory: Get the number of threads set on this object.
getOptimiser() - Method in class org.tribuo.math.optimisers.GradientOptimiserOptions: Gets the configured gradient optimiser.
getProvenance() - Method in class org.tribuo.math.distance.CosineDistance
getProvenance() - Method in class org.tribuo.math.distance.L1Distance
getProvenance() - Method in class org.tribuo.math.distance.L2Distance
getProvenance() - Method in class org.tribuo.math.kernel.Linear
getProvenance() - Method in class org.tribuo.math.kernel.Polynomial
getProvenance() - Method in class org.tribuo.math.kernel.RBF
getProvenance() - Method in class org.tribuo.math.kernel.Sigmoid
getProvenance() - Method in interface org.tribuo.math.neighbour.NeighboursQueryFactory
getProvenance() - Method in class org.tribuo.math.optimisers.AdaDelta
getProvenance() - Method in class org.tribuo.math.optimisers.AdaGrad
getProvenance() - Method in class org.tribuo.math.optimisers.AdaGradRDA
getProvenance() - Method in class org.tribuo.math.optimisers.Adam
getProvenance() - Method in class org.tribuo.math.optimisers.ParameterAveraging
getProvenance() - Method in class org.tribuo.math.optimisers.Pegasos
getProvenance() - Method in class org.tribuo.math.optimisers.RMSProp
getProvenance() - Method in class org.tribuo.math.optimisers.SGD
getReference() - Method in interface org.tribuo.math.la.MatrixIterator: Gets the MatrixTuple reference that this iterator updates.
getReference() - Method in interface org.tribuo.math.la.VectorIterator: Gets the reference to the VectorTuple this iterator updates.
getRow(int) - Method in class org.tribuo.math.la.DenseMatrix
getRow(int) - Method in class org.tribuo.math.la.DenseSparseMatrix
getRow(int) - Method in interface org.tribuo.math.la.Matrix: An SGDVector view of the row.
getShape() - Method in class org.tribuo.math.la.DenseMatrix
getShape() - Method in class org.tribuo.math.la.DenseSparseMatrix
getShape() - Method in class org.tribuo.math.la.DenseVector
getShape() - Method in class org.tribuo.math.la.SparseVector
getShape() - Method in interface org.tribuo.math.la.Tensor: Returns an int array specifying the shape of this Tensor.
getSimpleSGD(double) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a constant learning rate set to learningRate.
getSimpleSGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a constant learning rate set to learningRate, with momentum.
getSqrtDecaySGD(double) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a sqrt decaying learning rate initialised to learningRate.
getSqrtDecaySGD(double, double, SGD.Momentum) - Static method in class org.tribuo.math.optimisers.SGD: Generates an SGD optimiser with a sqrt decaying learning rate initialised to learningRate, with momentum.
getWeightMatrix() - Method in class org.tribuo.math.LinearParameters: Returns the weight matrix.
GradientOptimiserOptions - Class in org.tribuo.math.optimisers: CLI options for configuring a gradient optimiser.
GradientOptimiserOptions() - Constructor for class org.tribuo.math.optimisers.GradientOptimiserOptions
GradientOptimiserOptions.StochasticGradientOptimiserType - Enum in org.tribuo.math.optimisers: Type of the gradient optimisers available in CLIs.
gradients(Pair<Double, SGDVector>, SGDVector) - Method in interface org.tribuo.math.FeedForwardParameters: Generates the parameter gradients given the loss, output gradient and input features.
gradients(Pair<Double, SGDVector>, SGDVector) - Method in class org.tribuo.math.LinearParameters: Generate the gradients for a particular feature vector given the loss and the per output gradients.

H

hadamardProductInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor: Same as Tensor.hadamardProductInPlace(org.tribuo.math.la.Tensor, java.util.function.DoubleUnaryOperator), but applies the identity function.
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix: Only implemented for DenseMatrix.
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
hadamardProductInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor: Updates this Tensor with the Hadamard product (i.e., a term by term multiply) of this and other.
hashCode() - Method in class org.tribuo.math.distance.CosineDistance
hashCode() - Method in class org.tribuo.math.distance.L1Distance
hashCode() - Method in class org.tribuo.math.distance.L2Distance
hashCode() - Method in class org.tribuo.math.kernel.Linear
hashCode() - Method in class org.tribuo.math.kernel.Polynomial
hashCode() - Method in class org.tribuo.math.kernel.RBF
hashCode() - Method in class org.tribuo.math.kernel.Sigmoid
hashCode() - Method in class org.tribuo.math.la.DenseMatrix
hashCode() - Method in class org.tribuo.math.la.DenseSparseMatrix
hashCode() - Method in class org.tribuo.math.la.DenseVector
hashCode() - Method in class org.tribuo.math.la.MatrixTuple
hashCode() - Method in class org.tribuo.math.la.SparseVector
hashCode() - Method in class org.tribuo.math.la.VectorTuple
hashCode() - Method in class org.tribuo.math.LinearParameters
hashCode() - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory
hashCode() - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory
hashCode() - Method in class org.tribuo.math.util.ExpNormalizer
hashCode() - Method in class org.tribuo.math.util.HeapMerger
hashCode() - Method in class org.tribuo.math.util.MatrixHeapMerger
hashCode() - Method in class org.tribuo.math.util.NoopNormalizer
hashCode() - Method in class org.tribuo.math.util.Normalizer
hashCode() - Method in class org.tribuo.math.util.SigmoidNormalizer
HeapMerger - Class in org.tribuo.math.util: Merges each SparseVector separately using a PriorityQueue as a heap.
HeapMerger() - Constructor for class org.tribuo.math.util.HeapMerger: Constructs a HeapMerger.
householderMatrix() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: The Householder matrix produced during the tridiagonalisation.

I

i - Variable in class org.tribuo.math.la.MatrixTuple: The i index.
index - Variable in class org.tribuo.math.la.VectorTuple: The current index.
indexOfMax() - Method in class org.tribuo.math.la.DenseVector
indexOfMax() - Method in interface org.tribuo.math.la.SGDVector: Returns the index of the maximum value.
indexOfMax() - Method in class org.tribuo.math.la.SparseVector
indexOfMax() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
indices - Variable in class org.tribuo.math.la.SparseVector: The indices array.
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaDelta
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGrad
initialise(Parameters) - Method in class org.tribuo.math.optimisers.AdaGradRDA
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Adam
initialise(Parameters) - Method in class org.tribuo.math.optimisers.ParameterAveraging
initialise(Parameters) - Method in class org.tribuo.math.optimisers.Pegasos
initialise(Parameters) - Method in class org.tribuo.math.optimisers.RMSProp
initialise(Parameters) - Method in class org.tribuo.math.optimisers.SGD
initialise(Parameters) - Method in interface org.tribuo.math.StochasticGradientOptimiser: Initialises the gradient optimiser.
initialLearningRate - Variable in class org.tribuo.math.optimisers.SGD: The initial learning rate.
intersectAndAddInPlace(Tensor) - Method in interface org.tribuo.math.la.Tensor: Same as Tensor.intersectAndAddInPlace(org.tribuo.math.la.Tensor, java.util.function.DoubleUnaryOperator), but applies the identity function.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseMatrix
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseSparseMatrix: Only implemented for DenseMatrix.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.la.SparseVector
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in interface org.tribuo.math.la.Tensor: Updates this Tensor by adding all the values from the intersection with other.
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
intersectAndAddInPlace(Tensor, DoubleUnaryOperator) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
intersection(SparseVector) - Method in class org.tribuo.math.la.SparseVector: Generates an array of the indices that are active in both this vector and other
inverse() - Method in interface org.tribuo.math.la.Matrix.Factorization: Generates the inverse of the matrix with this factorization.
isSquare() - Method in class org.tribuo.math.la.DenseMatrix: Is this a square matrix?
isSymmetric() - Method in class org.tribuo.math.la.DenseMatrix: Returns true if this matrix is square and symmetric.
iteration - Variable in class org.tribuo.math.optimisers.SGD: The iteration number, in steps.
iterator() - Method in class org.tribuo.math.la.DenseMatrix
iterator() - Method in class org.tribuo.math.la.DenseSparseMatrix
iterator() - Method in class org.tribuo.math.la.DenseVector
iterator() - Method in class org.tribuo.math.la.SparseVector
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
iterator() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector

J

j - Variable in class org.tribuo.math.la.MatrixTuple: The j index.

K

KD_TREE - Enum constant in enum org.tribuo.math.neighbour.NeighboursQueryFactoryType: A factory which emits nearest neighbour query objects using a k-d tree search.
KDTree - Class in org.tribuo.math.neighbour.kdtree: A k-d tree nearest neighbour query implementation.
KDTreeFactory - Class in org.tribuo.math.neighbour.kdtree: A factory which creates k-d tree nearest neighbour query objects.
KDTreeFactory(Distance, int) - Constructor for class org.tribuo.math.neighbour.kdtree.KDTreeFactory: Constructs a k-d tree nearest neighbor query factory object using the supplied parameters.
Kernel - Interface in org.tribuo.math.kernel: An interface for a Mercer kernel function.

L

L1 - Enum constant in enum org.tribuo.math.distance.DistanceType: L1 (or Manhattan) distance.
l1Distance(SGDVector) - Method in class org.tribuo.math.la.DenseVector: The l1 or Manhattan distance between this vector and the other vector.
l1Distance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: The l1 or Manhattan distance between this vector and the other vector.
l1Distance(SGDVector) - Method in class org.tribuo.math.la.SparseVector
L1Distance - Class in org.tribuo.math.distance: L1 (or Manhattan) distance.
L1Distance() - Constructor for class org.tribuo.math.distance.L1Distance: Constructs an L1 distance function.
L2 - Enum constant in enum org.tribuo.math.distance.DistanceType: L2 (or Euclidean) distance.
l2Distance(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Synonym for euclideanDistance.
L2Distance - Class in org.tribuo.math.distance: L2 (or Euclidean) distance.
L2Distance() - Constructor for class org.tribuo.math.distance.L2Distance: Constructs an L2 distance function.
lambda - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Lambda for Pegasos.
learningRate - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Learning rate for AdaGrad, AdaGradRDA, Adam, Pegasos.
learningRate() - Method in class org.tribuo.math.optimisers.SGD: Override to provide a function which calculates the learning rate.
leftMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix
leftMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseSparseMatrix
leftMultiply(SGDVector) - Method in interface org.tribuo.math.la.Matrix: Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
leftMultiply(SGDVector) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
Linear - Class in org.tribuo.math.kernel: A linear kernel, u.dot(v).
Linear() - Constructor for class org.tribuo.math.kernel.Linear: A linear kernel, u.dot(v).
LinearParameters - Class in org.tribuo.math: A Parameters for producing linear models.
LinearParameters(int, int) - Constructor for class org.tribuo.math.LinearParameters: Constructor.
LinearParameters(DenseMatrix) - Constructor for class org.tribuo.math.LinearParameters: Constructs a LinearParameters wrapped around a weight matrix.
LINEARSGD - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: SGD with a linear-decay learning rate.
lMatrix() - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization: The lower triangular factorized matrix.
logSumExp() - Method in class org.tribuo.math.la.DenseVector: Sums log probabilities.
lower() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: The lower triangular matrix, with ones on the diagonal.
luFactorization() - Method in class org.tribuo.math.la.DenseMatrix: Computes the LU factorization of a square matrix.

M

Matrix - Interface in org.tribuo.math.la: Interface for 2 dimensional Tensors.
Matrix.Factorization - Interface in org.tribuo.math.la: Interface for matrix factorizations.
MatrixHeapMerger - Class in org.tribuo.math.util: Merges each DenseSparseMatrix using a PriorityQueue as a heap on the MatrixIterator.
MatrixHeapMerger() - Constructor for class org.tribuo.math.util.MatrixHeapMerger: Constructs a HeapMerger.
MatrixIterator - Interface in org.tribuo.math.la: A Comparable Iterator over MatrixTuples.
matrixMultiply(Matrix) - Method in class org.tribuo.math.la.DenseMatrix
matrixMultiply(Matrix) - Method in class org.tribuo.math.la.DenseSparseMatrix
matrixMultiply(Matrix) - Method in interface org.tribuo.math.la.Matrix: Multiplies this Matrix by another Matrix returning a matrix of the appropriate size.
matrixMultiply(Matrix, boolean, boolean) - Method in class org.tribuo.math.la.DenseMatrix
matrixMultiply(Matrix, boolean, boolean) - Method in class org.tribuo.math.la.DenseSparseMatrix
matrixMultiply(Matrix, boolean, boolean) - Method in interface org.tribuo.math.la.Matrix: Multiplies this Matrix by another Matrix returning a matrix of the appropriate size.
MatrixTuple - Class in org.tribuo.math.la: A mutable tuple used to avoid allocation when iterating a matrix.
MatrixTuple() - Constructor for class org.tribuo.math.la.MatrixTuple: Constructs an empty matrix tuple.
MatrixTuple(int, int, int) - Constructor for class org.tribuo.math.la.MatrixTuple: Constructs a matrix tuple with the specified values.
maxValue() - Method in class org.tribuo.math.la.DenseVector
maxValue() - Method in interface org.tribuo.math.la.SGDVector: Returns the maximum value.
maxValue() - Method in class org.tribuo.math.la.SparseVector
maxValue() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
meanVariance() - Method in class org.tribuo.math.la.DenseVector: Compute the mean and variance of this vector.
merge(List<SparseVector>, int, int[], double[]) - Static method in class org.tribuo.math.util.HeapMerger: Merges a list of sparse vectors into a single sparse vector, summing the values.
merge(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.HeapMerger
merge(DenseSparseMatrix[]) - Method in class org.tribuo.math.util.MatrixHeapMerger
merge(DenseSparseMatrix[]) - Method in interface org.tribuo.math.util.Merger: Merges an array of DenseSparseMatrix into a single DenseSparseMatrix.
merge(SparseVector[]) - Method in class org.tribuo.math.util.HeapMerger
merge(SparseVector[]) - Method in class org.tribuo.math.util.MatrixHeapMerger
merge(SparseVector[]) - Method in interface org.tribuo.math.util.Merger: Merges an array of SparseVector into a single SparseVector.
merge(Tensor[][], int) - Method in class org.tribuo.math.LinearParameters
merge(Tensor[][], int) - Method in interface org.tribuo.math.Parameters: Merge together an array of gradient arrays.
Merger - Interface in org.tribuo.math.util: An interface for merging an array of DenseSparseMatrix into a single DenseSparseMatrix.
minValue() - Method in class org.tribuo.math.la.DenseVector
minValue() - Method in interface org.tribuo.math.la.SGDVector: Returns the minimum value.
minValue() - Method in class org.tribuo.math.la.SparseVector
minValue() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
momentum - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Use momentum in SGD.
MultivariateNormalDistribution - Class in org.tribuo.math.distributions: A class for sampling from multivariate normal distributions.
MultivariateNormalDistribution(double[], double[][], long) - Constructor for class org.tribuo.math.distributions.MultivariateNormalDistribution: Constructs a multivariate normal distribution that can be sampled from.
MultivariateNormalDistribution(double[], double[][], long, boolean) - Constructor for class org.tribuo.math.distributions.MultivariateNormalDistribution: Constructs a multivariate normal distribution that can be sampled from.
MultivariateNormalDistribution(DenseVector, DenseMatrix, long) - Constructor for class org.tribuo.math.distributions.MultivariateNormalDistribution: Constructs a multivariate normal distribution that can be sampled from.
MultivariateNormalDistribution(DenseVector, DenseMatrix, long, boolean) - Constructor for class org.tribuo.math.distributions.MultivariateNormalDistribution: Constructs a multivariate normal distribution that can be sampled from.

N

NeighboursBruteForce - Class in org.tribuo.math.neighbour.bruteforce: A brute-force nearest neighbour query implementation.
NeighboursBruteForceFactory - Class in org.tribuo.math.neighbour.bruteforce: A factory which creates brute-force nearest neighbour query objects.
NeighboursBruteForceFactory(Distance, int) - Constructor for class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory: Constructs a brute-force nearest neighbor query factory object using the supplied parameters.
NeighboursQuery - Interface in org.tribuo.math.neighbour: An interface for nearest neighbour query objects.
NeighboursQueryFactory - Interface in org.tribuo.math.neighbour: An interface for factories which create nearest neighbour query objects.
NeighboursQueryFactoryType - Enum in org.tribuo.math.neighbour: These are the supported neighbour query implementations.
NESTEROV - Enum constant in enum org.tribuo.math.optimisers.SGD.Momentum: Nesterov momentum.
NONE - Enum constant in enum org.tribuo.math.optimisers.SGD.Momentum: No momentum.
nonSingular() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Returns true if all the eigenvalues are non-zero.
NoopNormalizer - Class in org.tribuo.math.util: NoopNormalizer returns a copy in NoopNormalizer.normalize(double[]) and is a no-op in place.
NoopNormalizer() - Constructor for class org.tribuo.math.util.NoopNormalizer: Constructs a NoopNormalizer.
normalize(double[]) - Method in class org.tribuo.math.util.ExpNormalizer
normalize(double[]) - Method in class org.tribuo.math.util.NoopNormalizer
normalize(double[]) - Method in class org.tribuo.math.util.Normalizer
normalize(double[]) - Method in class org.tribuo.math.util.SigmoidNormalizer
normalize(double[]) - Method in interface org.tribuo.math.util.VectorNormalizer: Normalizes the input array in some fashion specified by the class.
normalize(VectorNormalizer) - Method in class org.tribuo.math.la.DenseVector
normalize(VectorNormalizer) - Method in interface org.tribuo.math.la.SGDVector: Normalizes the vector using the supplied vector normalizer.
normalize(VectorNormalizer) - Method in class org.tribuo.math.la.SparseVector
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.ExpNormalizer
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.NoopNormalizer
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.Normalizer
normalizeInPlace(double[]) - Method in class org.tribuo.math.util.SigmoidNormalizer
normalizeInPlace(double[]) - Method in interface org.tribuo.math.util.VectorNormalizer: In place normalization of the array.
Normalizer - Class in org.tribuo.math.util: Normalizes, but first subtracts the minimum value (to ensure positivity).
Normalizer() - Constructor for class org.tribuo.math.util.Normalizer: Constructs a Normalizer.
normalizeRows(VectorNormalizer) - Method in class org.tribuo.math.la.DenseMatrix: Normalizes each row using the supplied normalizer in place.
numActiveElements() - Method in class org.tribuo.math.la.DenseVector
numActiveElements() - Method in interface org.tribuo.math.la.SGDVector: Returns the number of non-zero elements (on construction, an element could be set to zero and it would still remain active).
numActiveElements() - Method in class org.tribuo.math.la.SparseVector
numActiveElements(int) - Method in class org.tribuo.math.la.DenseMatrix
numActiveElements(int) - Method in class org.tribuo.math.la.DenseSparseMatrix
numActiveElements(int) - Method in interface org.tribuo.math.la.Matrix: The number of non-zero elements in that row.

O

oddSwaps() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: Is there an odd number of row swaps (used to compute the determinant).
offDiagonal() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: The off diagonal vector, with the first element set to zero.
oneNorm() - Method in class org.tribuo.math.la.DenseVector
oneNorm() - Method in interface org.tribuo.math.la.SGDVector: Calculates the Manhattan norm for this vector.
oneNorm() - Method in class org.tribuo.math.la.SparseVector
ONNXMathUtils - Class in org.tribuo.math.onnx: Tribuo Math specific helper functions for building ONNX protos.
org.tribuo.math - package org.tribuo.math: Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of math related utils.
org.tribuo.math.distance - package org.tribuo.math.distance: An interface for distance computations between two SGDVector instances along with some standard implementations.
org.tribuo.math.distributions - package org.tribuo.math.distributions: A package of statistical distributions.
org.tribuo.math.kernel - package org.tribuo.math.kernel: Provides a Kernel interface for Mercer kernels, along with implementations of standard kernels.
org.tribuo.math.la - package org.tribuo.math.la: Provides a linear algebra system used for numerical operations in Tribuo.
org.tribuo.math.neighbour - package org.tribuo.math.neighbour: Provides nearest neighbour query functionality.
org.tribuo.math.neighbour.bruteforce - package org.tribuo.math.neighbour.bruteforce: Provides a brute-force nearest neighbour query implementation.
org.tribuo.math.neighbour.kdtree - package org.tribuo.math.neighbour.kdtree: Provides a k-d tree nearest neighbour query implementation.
org.tribuo.math.onnx - package org.tribuo.math.onnx: Utilities for converting Tribuo math objects into ONNX representations.
org.tribuo.math.optimisers - package org.tribuo.math.optimisers: Provides implementations of StochasticGradientOptimiser.
org.tribuo.math.optimisers.util - package org.tribuo.math.optimisers.util: Provides some utility tensors for use in gradient optimisers.
org.tribuo.math.util - package org.tribuo.math.util: Provides math related util classes.
outer(SGDVector) - Method in class org.tribuo.math.la.DenseVector
outer(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Generates the matrix representing the outer product between the two vectors.
outer(SGDVector) - Method in class org.tribuo.math.la.SparseVector: This generates the outer product when dotted with another SparseVector.

P

paramAve - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Use parameter averaging.
ParameterAveraging - Class in org.tribuo.math.optimisers: Averages the parameters across a gradient run.
ParameterAveraging(StochasticGradientOptimiser) - Constructor for class org.tribuo.math.optimisers.ParameterAveraging: Adds parameter averaging around a gradient optimiser.
Parameters - Interface in org.tribuo.math: An interface to a Tensor[] array which accepts updates to the parameters.
Pegasos - Class in org.tribuo.math.optimisers: An implementation of the Pegasos gradient optimiser used primarily for solving the SVM problem.
Pegasos(double, double) - Constructor for class org.tribuo.math.optimisers.Pegasos: Constructs a Pegasos optimiser with the specified parameters.
PEGASOS - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The Pegasos optimiser.
permutationArr() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: The row permutations applied to get this factorization.
permutationMatrix() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: The row permutations stored as a sparse matrix of ones.
Polynomial - Class in org.tribuo.math.kernel: A polynomial kernel, (gamma*u.dot(v) + intercept)^degree.
Polynomial(double, double, double) - Constructor for class org.tribuo.math.kernel.Polynomial: A polynomial kernel, (gamma*u.dot(v) + intercept)^degree.
positiveEigenvalues() - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Returns true if all the eigenvalues are positive.
postConfig() - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory: Used by the OLCUT configuration system, and should not be called by external code.
postConfig() - Method in class org.tribuo.math.optimisers.RMSProp: Used by the OLCUT configuration system, and should not be called by external code.
predict(SGDVector) - Method in interface org.tribuo.math.FeedForwardParameters: Generates an un-normalized prediction by feeding the features through the parameters.
predict(SGDVector) - Method in class org.tribuo.math.LinearParameters: Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.

Q

query(SGDVector[], int) - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForce
query(SGDVector[], int) - Method in class org.tribuo.math.neighbour.kdtree.KDTree
query(SGDVector[], int) - Method in interface org.tribuo.math.neighbour.NeighboursQuery: Queries a set of SGDVectors to determine the k points nearest to the provided points.
query(SGDVector, int) - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForce
query(SGDVector, int) - Method in class org.tribuo.math.neighbour.kdtree.KDTree
query(SGDVector, int) - Method in interface org.tribuo.math.neighbour.NeighboursQuery: Queries a set of SGDVectors to determine the k points nearest to the provided point.
queryAll(int) - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForce
queryAll(int) - Method in class org.tribuo.math.neighbour.kdtree.KDTree
queryAll(int) - Method in interface org.tribuo.math.neighbour.NeighboursQuery: Queries a set of SGDVectors to determine the k points nearest to every point in the set.

R

RBF - Class in org.tribuo.math.kernel: A Radial Basis Function (RBF) kernel, exp(-gamma*|u-v|^2).
RBF(double) - Constructor for class org.tribuo.math.kernel.RBF: A Radial Basis Function (RBF) kernel, exp(-gamma*|u-v|^2).
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in class org.tribuo.math.la.DenseVector: Performs a reduction from left to right of this vector.
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in interface org.tribuo.math.la.SGDVector: Reduces the vector, applying the transformation to every value (including the implicit zeros) and reducing the output by applying the supplied reduction operator (where the right argument is the current reduction value, and the left argument is the transformed value).
reduce(double, DoubleUnaryOperator, DoubleBinaryOperator) - Method in class org.tribuo.math.la.SparseVector
reduce(T, DoubleUnaryOperator, BiFunction<Double, T, T>) - Method in class org.tribuo.math.la.DenseVector: Performs a reduction from left to right of this vector.
reset() - Method in class org.tribuo.math.optimisers.AdaDelta
reset() - Method in class org.tribuo.math.optimisers.AdaGrad
reset() - Method in class org.tribuo.math.optimisers.AdaGradRDA
reset() - Method in class org.tribuo.math.optimisers.Adam
reset() - Method in class org.tribuo.math.optimisers.ParameterAveraging
reset() - Method in class org.tribuo.math.optimisers.Pegasos
reset() - Method in class org.tribuo.math.optimisers.RMSProp
reset() - Method in class org.tribuo.math.optimisers.SGD
reset() - Method in interface org.tribuo.math.StochasticGradientOptimiser: Resets the optimiser so it's ready to optimise a new Parameters.
reshape(int[]) - Method in class org.tribuo.math.la.DenseMatrix
reshape(int[]) - Method in class org.tribuo.math.la.DenseSparseMatrix
reshape(int[]) - Method in class org.tribuo.math.la.DenseVector
reshape(int[]) - Method in class org.tribuo.math.la.SparseVector
reshape(int[]) - Method in interface org.tribuo.math.la.Tensor: Reshapes the Tensor to the supplied shape.
rho - Variable in class org.tribuo.math.optimisers.GradientOptimiserOptions: Rho for RMSProp, AdaDelta, SGD with Momentum.
rho - Variable in class org.tribuo.math.optimisers.SGD: The scaling factor for the momentum.
rightMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix
rightMultiply(SGDVector) - Method in class org.tribuo.math.la.DenseSparseMatrix: rightMultiply is very inefficient on DenseSparseMatrix due to the storage format.
rightMultiply(SGDVector) - Method in interface org.tribuo.math.la.Matrix: Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
RMSProp - Class in org.tribuo.math.optimisers: An implementation of the RMSProp gradient optimiser.
RMSProp(double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp: Constructs an RMSProp gradient optimiser using the specified parameters with epsilon set to 1e-8 and decay to 0.0.
RMSProp(double, double, double, double) - Constructor for class org.tribuo.math.optimisers.RMSProp: Constructs an RMSProp gradient optimiser using the specified parameters.
RMSPROP - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: The RMSProp optimiser.
rowScaleInPlace(DenseVector) - Method in class org.tribuo.math.la.DenseMatrix
rowScaleInPlace(DenseVector) - Method in class org.tribuo.math.la.DenseSparseMatrix
rowScaleInPlace(DenseVector) - Method in interface org.tribuo.math.la.Matrix: Scales each row by the appropriate value in the DenseVector.
rowSum() - Method in class org.tribuo.math.la.DenseMatrix
rowSum() - Method in class org.tribuo.math.la.DenseSparseMatrix
rowSum() - Method in interface org.tribuo.math.la.Matrix: Generates a DenseVector representing the sum of each row.
rowSum(int) - Method in class org.tribuo.math.la.DenseMatrix: Calculates the sum of the specified row.

S

sampleArray() - Method in class org.tribuo.math.distributions.MultivariateNormalDistribution: Sample a vector from this multivariate normal distribution.
sampleVector() - Method in class org.tribuo.math.distributions.MultivariateNormalDistribution: Sample a vector from this multivariate normal distribution.
scalarAddInPlace(double) - Method in interface org.tribuo.math.la.Tensor: Adds scalar to each element of this Tensor.
scale(double) - Method in class org.tribuo.math.la.DenseVector
scale(double) - Method in interface org.tribuo.math.la.SGDVector: Generates a new vector with each element scaled by coefficient.
scale(double) - Method in class org.tribuo.math.la.SparseVector
scaleInPlace(double) - Method in interface org.tribuo.math.la.Tensor: Scales each element of this Tensor by coefficient.
scaleInPlace(double) - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
scaleInPlace(double) - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
selectColumns(int[]) - Method in class org.tribuo.math.la.DenseMatrix: Returns a new DenseMatrix containing a copy of the selected columns.
selectColumns(List<Integer>) - Method in class org.tribuo.math.la.DenseMatrix: Returns a new DenseMatrix containing a copy of the selected columns.
serialize() - Method in class org.tribuo.math.distance.CosineDistance
serialize() - Method in class org.tribuo.math.distance.L1Distance
serialize() - Method in class org.tribuo.math.distance.L2Distance
serialize() - Method in class org.tribuo.math.kernel.Linear
serialize() - Method in class org.tribuo.math.kernel.Polynomial
serialize() - Method in class org.tribuo.math.kernel.RBF
serialize() - Method in class org.tribuo.math.kernel.Sigmoid
serialize() - Method in class org.tribuo.math.la.DenseMatrix
serialize() - Method in class org.tribuo.math.la.DenseSparseMatrix
serialize() - Method in class org.tribuo.math.la.DenseVector
serialize() - Method in class org.tribuo.math.la.SparseVector
serialize() - Method in class org.tribuo.math.LinearParameters
serialize() - Method in class org.tribuo.math.neighbour.bruteforce.NeighboursBruteForceFactory
serialize() - Method in class org.tribuo.math.neighbour.kdtree.KDTreeFactory
serialize() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
serialize() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
serialize() - Method in class org.tribuo.math.util.ExpNormalizer
serialize() - Method in class org.tribuo.math.util.HeapMerger
serialize() - Method in class org.tribuo.math.util.MatrixHeapMerger
serialize() - Method in class org.tribuo.math.util.NoopNormalizer
serialize() - Method in class org.tribuo.math.util.Normalizer
serialize() - Method in class org.tribuo.math.util.SigmoidNormalizer
set(double) - Method in class org.tribuo.math.la.DenseVector: Sets all elements of this vector to value.
set(int, double) - Method in class org.tribuo.math.la.DenseVector
set(int, double) - Method in interface org.tribuo.math.la.SGDVector: Sets the index to the value.
set(int, double) - Method in class org.tribuo.math.la.SparseVector
set(int, int, double) - Method in class org.tribuo.math.la.DenseMatrix
set(int, int, double) - Method in class org.tribuo.math.la.DenseSparseMatrix
set(int, int, double) - Method in interface org.tribuo.math.la.Matrix: Sets an element at the supplied location.
set(Tensor[]) - Method in class org.tribuo.math.LinearParameters
set(Tensor[]) - Method in interface org.tribuo.math.Parameters: Set the underlying Tensor array to newWeights.
setColumn(int, SGDVector) - Method in class org.tribuo.math.la.DenseMatrix: Sets the column to the supplied vector value.
setElements(DenseVector) - Method in class org.tribuo.math.la.DenseVector: Sets all the elements of this vector to be the same as other.
SGD - Class in org.tribuo.math.optimisers: An implementation of single learning rate SGD and optionally momentum.
SGD() - Constructor for class org.tribuo.math.optimisers.SGD: For olcut.
SGD.Momentum - Enum in org.tribuo.math.optimisers: Momentum types.
sgdType() - Method in class org.tribuo.math.optimisers.SGD: Override to specify the kind of SGD.
SGDVector - Interface in org.tribuo.math.la: Interface for 1 dimensional Tensors.
shapeCheck(Tensor, Tensor) - Static method in interface org.tribuo.math.la.Tensor: Checks that the two tensors have compatible shapes.
shapeSum(int[]) - Static method in interface org.tribuo.math.la.Tensor: The number of elements in this shape, i.e., the product of the shape array.
ShrinkingMatrix - Class in org.tribuo.math.optimisers.util: A subclass of DenseMatrix which shrinks the value every time a new value is added.
ShrinkingMatrix(DenseMatrix, double, boolean) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingMatrix: Constructs a shrinking matrix copy of the supplied dense matrix.
ShrinkingMatrix(DenseMatrix, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingMatrix: Constructs a shrinking matrix copy of the supplied dense matrix.
ShrinkingTensor - Interface in org.tribuo.math.optimisers.util: An interface which tags a Tensor with a convertToDense method.
ShrinkingVector - Class in org.tribuo.math.optimisers.util: A subclass of DenseVector which shrinks the value every time a new value is added.
ShrinkingVector(DenseVector, double, boolean) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingVector: Constructs a shrinking vector copy of the supplied dense matrix.
ShrinkingVector(DenseVector, double, double) - Constructor for class org.tribuo.math.optimisers.util.ShrinkingVector: Constructs a shrinking vector copy of the supplied dense vector.
sigmoid(double) - Static method in class org.tribuo.math.util.SigmoidNormalizer: A logistic sigmoid function.
Sigmoid - Class in org.tribuo.math.kernel: A sigmoid kernel, tanh(gamma*u.dot(v) + intercept).
Sigmoid(double, double) - Constructor for class org.tribuo.math.kernel.Sigmoid: A sigmoid kernel, tanh(gamma*u.dot(v) + intercept).
SigmoidNormalizer - Class in org.tribuo.math.util: Normalizes the input by applying a logistic sigmoid to each element.
SigmoidNormalizer() - Constructor for class org.tribuo.math.util.SigmoidNormalizer: Constructs a Normalizer.
similarity(SparseVector, SparseVector) - Method in interface org.tribuo.math.kernel.Kernel: Calculates the similarity between two SparseVectors.
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Linear
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Polynomial
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.RBF
similarity(SparseVector, SparseVector) - Method in class org.tribuo.math.kernel.Sigmoid
size() - Method in class org.tribuo.math.la.DenseVector
size() - Method in interface org.tribuo.math.la.SGDVector: Returns the dimensionality of this vector.
size() - Method in class org.tribuo.math.la.SparseVector
solve(Matrix) - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization: Solves the system A * X = B, where B is the input matrix, and A is the matrix which produced this Cholesky factorization.
solve(Matrix) - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Solves the system A * X = Y, where Y is the input matrix, and A is the matrix which produced this eigen decomposition.
solve(Matrix) - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: Solves the system A * X = Y, where Y is the input matrix, and A is the matrix which produced this LU factorization.
solve(Matrix) - Method in interface org.tribuo.math.la.Matrix.Factorization: Solves the system A * X = Y, where Y is the input matrix, and A is the matrix which produced this factorization.
solve(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix.CholeskyFactorization: Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this Cholesky factorization, and b is the returned value.
solve(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix.EigenDecomposition: Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this eigen decomposition, and b is the returned value.
solve(SGDVector) - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this LU factorization, and b is the returned value.
solve(SGDVector) - Method in interface org.tribuo.math.la.Matrix.Factorization: Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this factorization, and b is the returned value.
SparseVector - Class in org.tribuo.math.la: A sparse vector.
SparseVector(int, int[], double) - Constructor for class org.tribuo.math.la.SparseVector: Creates a sparse vector of the specified size, with the supplied value at each of the indices.
sparsify() - Method in class org.tribuo.math.la.DenseVector: Generates a SparseVector representation from this dense vector, removing all values with absolute value below VectorTuple.DELTA.
sparsify(double) - Method in class org.tribuo.math.la.DenseVector: Generates a SparseVector representation from this dense vector, removing all values with absolute value below the supplied tolerance.
SQRTSGD - Enum constant in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: SGD with a square root decay learning rate.
STANDARD - Enum constant in enum org.tribuo.math.optimisers.SGD.Momentum: Standard momentum.
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaDelta
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaGrad
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.AdaGradRDA
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.Adam
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.ParameterAveraging: This passes the gradient update to the inner optimiser, then updates the average weight values.
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.Pegasos
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.RMSProp
step(Tensor[], double) - Method in class org.tribuo.math.optimisers.SGD
step(Tensor[], double) - Method in interface org.tribuo.math.StochasticGradientOptimiser: Take a Tensor array of gradients and transform them according to the current weight and learning rates.
StochasticGradientOptimiser - Interface in org.tribuo.math: Interface for gradient based optimisation methods.
subtract(SGDVector) - Method in class org.tribuo.math.la.DenseVector: Subtracts other from this vector, producing a new DenseVector.
subtract(SGDVector) - Method in interface org.tribuo.math.la.SGDVector: Subtracts other from this vector, producing a new SGDVector.
subtract(SGDVector) - Method in class org.tribuo.math.la.SparseVector: Subtracts other from this vector, producing a new SGDVector.
sum() - Method in class org.tribuo.math.la.DenseVector
sum() - Method in interface org.tribuo.math.la.SGDVector: Calculates the sum of this vector.
sum() - Method in class org.tribuo.math.la.SparseVector
sum() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
sum(DoubleUnaryOperator) - Method in class org.tribuo.math.la.DenseVector: Sums this vector, applying the supplied function to each element first.

T

Tensor - Interface in org.tribuo.math.la: An interface for Tensors, currently Vectors and Matrices.
toArray() - Method in class org.tribuo.math.la.DenseMatrix: Returns a copy of this matrix as a 2d array.
toArray() - Method in class org.tribuo.math.la.DenseVector: Generates a copy of the values in this DenseVector.
toArray() - Method in interface org.tribuo.math.la.SGDVector: Returns an array containing all the values in the vector (including any implicit zeros).
toArray() - Method in class org.tribuo.math.la.SparseVector
toArray() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector
toDenseArray() - Method in class org.tribuo.math.la.SparseVector: Deprecated.
tolerance - Static variable in interface org.tribuo.math.optimisers.util.ShrinkingTensor: The tolerance below which the scale factor is applied to the stored values and reset to 1.0.
toString() - Method in class org.tribuo.math.distance.CosineDistance
toString() - Method in class org.tribuo.math.distance.L1Distance
toString() - Method in class org.tribuo.math.distance.L2Distance
toString() - Method in class org.tribuo.math.distributions.MultivariateNormalDistribution
toString() - Method in class org.tribuo.math.kernel.Linear
toString() - Method in class org.tribuo.math.kernel.Polynomial
toString() - Method in class org.tribuo.math.kernel.RBF
toString() - Method in class org.tribuo.math.kernel.Sigmoid
toString() - Method in class org.tribuo.math.la.DenseMatrix
toString() - Method in class org.tribuo.math.la.DenseSparseMatrix
toString() - Method in class org.tribuo.math.la.DenseVector
toString() - Method in class org.tribuo.math.la.MatrixTuple
toString() - Method in class org.tribuo.math.la.SparseVector
toString() - Method in class org.tribuo.math.la.VectorTuple
toString() - Method in class org.tribuo.math.optimisers.AdaDelta
toString() - Method in class org.tribuo.math.optimisers.AdaGrad
toString() - Method in class org.tribuo.math.optimisers.AdaGradRDA
toString() - Method in class org.tribuo.math.optimisers.Adam
toString() - Method in class org.tribuo.math.optimisers.ParameterAveraging
toString() - Method in class org.tribuo.math.optimisers.Pegasos
toString() - Method in class org.tribuo.math.optimisers.RMSProp
toString() - Method in class org.tribuo.math.optimisers.SGD
transpose() - Method in class org.tribuo.math.la.DenseMatrix: Returns a transposed copy of this matrix.
transpose(Dataset<T>) - Static method in class org.tribuo.math.la.SparseVector: Converts a dataset of row-major examples into an array of column-major sparse vectors.
transpose(Dataset<T>, ImmutableFeatureMap) - Static method in class org.tribuo.math.la.SparseVector: Converts a dataset of row-major examples into an array of column-major sparse vectors.
transpose(SparseVector[]) - Static method in class org.tribuo.math.la.SparseVector: Transposes an array of sparse vectors from row-major to column-major or vice versa.
twoNorm() - Method in class org.tribuo.math.la.DenseMatrix
twoNorm() - Method in class org.tribuo.math.la.DenseSparseMatrix
twoNorm() - Method in class org.tribuo.math.la.DenseVector
twoNorm() - Method in interface org.tribuo.math.la.SGDVector: Calculates the euclidean norm for this vector.
twoNorm() - Method in class org.tribuo.math.la.SparseVector
twoNorm() - Method in interface org.tribuo.math.la.Tensor: Calculates the euclidean norm for this vector.
twoNorm() - Method in class org.tribuo.math.optimisers.util.ShrinkingMatrix
twoNorm() - Method in class org.tribuo.math.optimisers.util.ShrinkingVector

U

unpackProto(DenseTensorProto) - Static method in class org.tribuo.math.la.DenseMatrix: Unpacks a DenseTensorProto into a DenseMatrix.
unpackProto(DenseTensorProto) - Static method in class org.tribuo.math.la.DenseVector: Unpacks a DenseTensorProto into a DenseVector.
update(Tensor[]) - Method in class org.tribuo.math.LinearParameters
update(Tensor[]) - Method in interface org.tribuo.math.Parameters: Apply gradients to the parameters.
upper() - Method in class org.tribuo.math.la.DenseMatrix.LUFactorization: The upper triangular matrix.
useMomentum - Variable in class org.tribuo.math.optimisers.SGD: Should it use momentum.

V

value - Variable in class org.tribuo.math.la.MatrixTuple: The value.
value - Variable in class org.tribuo.math.la.VectorTuple: The current value.
valueOf(String) - Static method in enum org.tribuo.math.distance.DistanceType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.math.neighbour.NeighboursQueryFactoryType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.tribuo.math.optimisers.SGD.Momentum: Returns the enum constant of this type with the specified name.
values - Variable in class org.tribuo.math.la.DenseMatrix: The value array.
values - Variable in class org.tribuo.math.la.SparseVector: The values array.
values() - Static method in enum org.tribuo.math.distance.DistanceType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.math.neighbour.NeighboursQueryFactoryType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.math.optimisers.GradientOptimiserOptions.StochasticGradientOptimiserType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.tribuo.math.optimisers.SGD.Momentum: Returns an array containing the constants of this enum type, in the order they are declared.
variance() - Method in interface org.tribuo.math.la.SGDVector: Calculates the variance of this vector.
variance(double) - Method in class org.tribuo.math.la.DenseVector
variance(double) - Method in interface org.tribuo.math.la.SGDVector: Calculates the variance of this vector based on the supplied mean.
variance(double) - Method in class org.tribuo.math.la.SparseVector
VectorIterator - Interface in org.tribuo.math.la: A Comparable Iterator over VectorTuples.
VectorNormalizer - Interface in org.tribuo.math.util: A functional interface that generates a normalized version of a double array.
VectorTuple - Class in org.tribuo.math.la: A mutable tuple used to avoid allocation when iterating a vector.
VectorTuple() - Constructor for class org.tribuo.math.la.VectorTuple: Creates an empty vector tuple.
VectorTuple(int, int) - Constructor for class org.tribuo.math.la.VectorTuple: Creates a vector tuple with the specified values.

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