Package | Description |
---|---|
jsat.datatransform.kernel |
Modifier and Type | Method and Description |
---|---|
Nystrom.SamplingMethod |
Nystrom.getBasisSamplingMethod()
Returns the method of selecting the basis vectors
|
Nystrom.SamplingMethod |
KernelPCA.getBasisSamplingMethod()
Returns the method of selecting the basis vectors
|
static Nystrom.SamplingMethod |
Nystrom.SamplingMethod.valueOf(String name)
Returns the enum constant of this type with the specified name.
|
static Nystrom.SamplingMethod[] |
Nystrom.SamplingMethod.values()
Returns an array containing the constants of this enum type, in
the order they are declared.
|
Modifier and Type | Method and Description |
---|---|
static List<Vec> |
Nystrom.sampleBasisVectors(KernelTrick k,
DataSet dataset,
List<Vec> X,
Nystrom.SamplingMethod method,
int basisSize,
boolean sampleWithReplacment,
Random rand)
Performs sampling of a data set for a subset of the vectors that make a
good set of basis vectors for forming an approximation of a full kernel
space.
|
void |
Nystrom.setBasisSamplingMethod(Nystrom.SamplingMethod method)
Sets the method of selecting the basis vectors
|
void |
KernelPCA.setBasisSamplingMethod(Nystrom.SamplingMethod method)
Sets the method of selecting the basis vectors
|
Constructor and Description |
---|
KernelPCA(KernelTrick k,
DataSet ds,
int dimensions,
int basisSize,
Nystrom.SamplingMethod samplingMethod)
Creates a new Kernel PCA transform object
|
KernelPCA(KernelTrick k,
int dimensions,
int basisSize,
Nystrom.SamplingMethod samplingMethod)
Creates a new Kernel PCA transform object
|
Nystrom(KernelTrick k,
DataSet dataset,
int basisSize,
Nystrom.SamplingMethod method)
Creates a new Nystrom approximation object
|
Nystrom(KernelTrick k,
DataSet dataset,
int basisSize,
Nystrom.SamplingMethod method,
double ridge,
boolean sampleWithReplacment)
Creates a new Nystrom approximation object
|
Nystrom(KernelTrick k,
int basisSize,
Nystrom.SamplingMethod method,
double ridge,
boolean sampleWithReplacment)
Creates a new Nystrom approximation object
|
Copyright © 2017. All rights reserved.