Package com.aliasi.matrix

Classes for matrices and vectors.

See: Description

Interface Summary

Interface	Description
KernelFunction	A KernelFunction computes real-valued proximities between vectors.
Matrix	A Matrix represents a 2-dimensional matrix.
Vector	A Vector represents an n-dimensional value.

Class Summary

Class	Description
AbstractMatrix	An AbstractMatrix implements most of a matrix's functionality in terms of methods for accessing numbers of rows and columns and values.
AbstractVector	An AbstractVector implements most of a vector's functionality in terms of methods for dimensionality and values.
CosineDistance	The CosineDistance class implements proximity as vector cosine.
DenseMatrix	A DenseMatrix is a matrix implementation suitable for matrices with primarily non-zero values.
DenseVector	A DenseVector is a vector implementation suitable for vectors with primarily non-zero values.
DotProductKernel	The DotProductKernel is the trivial kernel function computed by taking the dot product of the input vectors.
EuclideanDistance	The EuclideanDistance class implements standard Euclidean distance between vectors.
GaussianRadialBasisKernel	A GaussianRadialBasisKernel provides a kernel based on a Gaussian radial basis function with a fixed variance parameter.
HyperbolicTangentKernel	A HyperbolicTangentKernel provides a kernel based on the hyperbolic tangent of a dot product with fixed linear scaling.
Matrices	The Matrices class contains static utility methods for various matrix properties and operations.
MinkowskiDistance	The MinkowskiDistance class implements Minkowski distance of a fixed order between vectors.
PolynomialKernel	A PolynomialKernel provides a dot product over a fixed degree polynomial basis expansion of a vector.
ProximityMatrix	A ProximityMatrix provides a pseudo-metric of proximities between points.
SparseFloatVector	A SparseFloatVector implements an immutable sparse vector with values represented as single-precision floating point numbers.
SvdMatrix	An SvdMatrix provides a means of storing a matrix that has been factored via a singular-value decomposition (SVD).
TaxicabDistance	The TaxicabDistance class implements standard taxicab, or Manhattan distance between vectors.

Package com.aliasi.matrix Description

Classes for matrices and vectors.