Package | Description |
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org.drip.learning.kernel | |
org.drip.learning.regularization | |
org.drip.spaces.functionclass | |
org.drip.spaces.rxtor1 |
Modifier and Type | Class and Description |
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class |
EigenFunctionRdToR1
EigEigenFunctionRdToR1enFunction holds the Eigen-vector Function and its corresponding Space of the R^d To
R^1 Kernel Linear Integral Operator defined by:
T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
1) Ash, R.
|
Modifier and Type | Method and Description |
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NormedRdToNormedR1 |
IntegralOperatorEigenComponent.rkhsFeatureMap()
Retrieve the Feature Map Space represented via the Reproducing Kernel Hilbert Space
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Modifier and Type | Class and Description |
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class |
RegularizerRdCombinatorialToR1Continuous
RegularizerRdCombinatorialToR1Continuous computes the Structural Loss and Risk for the specified Normed
R^d Combinatorial To Normed R^1 Continuous Learning Function.
|
class |
RegularizerRdContinuousToR1Continuous
RegularizerRdContinuousToR1Continuous computes the Structural Loss and Risk for the specified Normed R^d
Continuous To Normed R^1 Continuous Learning Function.
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Constructor and Description |
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NormedRdToNormedR1Finite(double dblMaureyConstant,
NormedRdToNormedR1[] aNormedRdToNormedR1)
NormedRdToNormedR1Finite Function Class Constructor
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Modifier and Type | Class and Description |
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class |
NormedRdCombinatorialToR1Continuous
NormedRdCombinatorialToR1Continuous implements the f : Validated Normed R^d Combinatorial To Validated
Normed R^1 Continuous Function Spaces.
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class |
NormedRdContinuousToR1Continuous
NormedRdContinuousToR1Continuous implements the f : Validated Normed R^d Continuous To Validated Normed
R^1 Continuous Function Spaces.
|