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 | 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. |