Package | Description |
---|---|
org.biojava.stats.svm |
Support Vector Machine classification and regression.
|
org.biojava.stats.svm.tools |
Tools for use of the SVM package.
|
Modifier and Type | Class and Description |
---|---|
class |
CachingKernel
Caches the results of a nested kernel so that k(a, b) need only be calculated
once.
|
class |
DiagonalAddKernel
Adds a class specific constant to k(x, x).
|
class |
DiagonalCachingKernel
Caches the leading diagonal of a kernel matrix.
|
class |
LinearKernel
Deprecated.
Just use SparseVector.kernel instead...
|
class |
ListSumKernel
This kernel computes the sum of the dot products between items of two lists
at corresponding indexes.
|
class |
NestedKernel
Encapsulates a kernel that wraps another kernel up.
|
class |
NormalizingKernel
Performs a normalization on the results of a nested kernel.
|
class |
PolynomialKernel
This kernel computes all possible products of order features in feature
space.
|
class |
RadialBaseKernel
This kernel computes the radial base kernel that corresponds to a gausian
distribution.
|
class |
SigmoidKernel
This kernel implements a three layer neural net.
|
static class |
SparseVector.NormalizingKernel
A version of the standard dot-product kernel that scales each column
independently.
|
Modifier and Type | Field and Description |
---|---|
static SVMKernel |
SparseVector.kernel |
Modifier and Type | Method and Description |
---|---|
SVMKernel |
SVMRegressionModel.getKernel() |
SVMKernel |
SVMClassifierModel.getKernel() |
SVMKernel |
SimpleSVMClassifierModel.getKernel() |
SVMKernel |
NestedKernel.getNestedKernel()
Retrieve the currently nested SVMKernel.
|
SVMKernel |
SigmoidKernel.getWrappedKernel() |
Modifier and Type | Method and Description |
---|---|
void |
SVMRegressionModel.setKernel(SVMKernel k) |
void |
NestedKernel.setNestedKernel(SVMKernel k)
Set the SVMKernel to nest to
k.
|
void |
DiagonalCachingKernel.setNestedKernel(SVMKernel k)
Set the kernel to nest.
|
void |
CachingKernel.setNestedKernel(SVMKernel k) |
void |
SigmoidKernel.setWrappedKernel(SVMKernel kernel) |
SVMClassifierModel |
SMOTrainer.trainModel(SVMTarget target,
SVMKernel kernel,
TrainingListener l) |
Constructor and Description |
---|
CachingKernel(SVMKernel k) |
DiagonalCachingKernel(SVMKernel k)
Creates a new DiagonalCachingKernel that nests k.
|
NestedKernel(SVMKernel k)
Create a new NestedKernel that wraps
k.
|
NormalizingKernel(SVMKernel k) |
PolynomialKernel(SVMKernel nested,
double order,
double a,
double c) |
RadialBaseKernel(SVMKernel nested,
double width) |
SimpleSVMClassifierModel(SVMKernel kernel) |
SimpleSVMClassifierModel(SVMKernel kernel,
Collection items) |
SimpleSVMClassifierModel(SVMKernel kernel,
SVMTarget target) |
Modifier and Type | Class and Description |
---|---|
class |
SuffixTreeKernel
Computes the dot-product of two suffix-trees as the sum of the products
of the counts of all nodes they have in common.
|
Modifier and Type | Field and Description |
---|---|
static SVMKernel |
ClassifierExample.PointClassifier.polyKernel |
static SVMKernel |
ClassifierExample.PointClassifier.rbfKernel |
Modifier and Type | Method and Description |
---|---|
SVMKernel |
ClassifierExample.PointClassifier.getKernel()
Retrieve the currently used kernel
|
Modifier and Type | Method and Description |
---|---|
void |
ClassifierExample.PointClassifier.setKernel(SVMKernel kernel)
Set the kernel used for classification.
|
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