Uses of Package
org.drip.learning.kernel
| Package | Description |
|---|---|
| org.drip.learning.kernel |
Statistical Learning Banach Mercer Kernels
|
| org.drip.learning.svm |
Kernel SVM Decision Function Operator
|
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Classes in org.drip.learning.kernel used by org.drip.learning.kernel Class Description DiagonalScalingOperator DiagonalScalingOperator implements the Scaling Operator that is used to determine the Bounds of the Rx L2 To Rx L2 Kernel Linear Integral Operator defined by: T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
Ash, R.EigenFunctionRdToR1 EigenFunctionRdToR1 holds the Eigen-vector Function and its corresponding Space of the Rd To R1 Kernel Linear Integral Operator defined by: T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
Ash, R.IntegralOperatorEigenComponent IntegralOperatorEigenComponent holds the Eigen-Function Space and the Eigenvalue Functions/Spaces of the Rx L2 To Rx L2 Kernel Linear Integral Operator defined by: T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
Ash, R.IntegralOperatorEigenContainer IntegralOperatorEigenContainer holds the Group of Eigen-Components that result from the Eigenization of the Rx L2 To Rx L2 Kernel Linear Integral Operator defined by: T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
Ash, R.SymmetricRdToNormedR1Kernel SymmetricRdToNormedR1Kernel exposes the Functionality behind the Kernel that is Normed Rd X Normed Rd To Supremum R1, that is, a Kernel that symmetric in the Input Metric Vector Space in terms of both the Metric and the Dimensionality. -
Classes in org.drip.learning.kernel used by org.drip.learning.svm Class Description DiagonalScalingOperator DiagonalScalingOperator implements the Scaling Operator that is used to determine the Bounds of the Rx L2 To Rx L2 Kernel Linear Integral Operator defined by: T_k [f(.)] := Integral Over Input Space {k (., y) * f(y) * d[Prob(y)]}
The References are:
Ash, R.SymmetricRdToNormedRdKernel SymmetricRdToNormedRdKernel exposes the Functionality behind the Kernel that is Normed Rd X Normed Rd To Normed Rd, that is, a Kernel that symmetric in the Input Metric Vector Space in terms of both the Metric and the Dimensionality.