Developer Guide for Intel® Data Analytics Acceleration Library 2016 Update 4

Batch Processing

Algorithm Input

The RBF kernel accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.

Input ID

Input

X

Pointer to the n x p numeric table that represents the matrix X. This table can be an object of any class derived from NumericTable.

Y

Pointer to the m x p numeric table that represents the matrix Y. This table can be an object of any class derived from NumericTable.

Algorithm Parameters

The RBF kernel has the following parameters:

Parameter

Default Value

Description

algorithmFPType

double

The floating-point type that the algorithm uses for intermediate computations. Can be float or double.

method

defaultDense

Available computation methods:

  • defaultDense - performance-oriented method
  • fastCSR - performance-oriented method for CSR numeric tables

ComputationMode

matrixMatrix

Computation mode for the kernel function. Can be:

  • vectorVector - compute the kernel function for given feature vectors xi and yj

  • matrixVector - compute the kernel function for all vectors in the set X and a given feature vector yj

  • matrixMatrix - compute the kernel function for all vectors in the sets X and Y.

    In Intel DAAL, this mode requires equal numbers of observations in both input tables: n=m.

rowIndexX

0

Index i of the vector in the set X for the vectorVector computation mode.

rowIndexY

0

Index j of the vector in the set Y for the vectorVector or matrixVector computation mode.

rowIndexResult

0

Row index in the values numeric table to locate the result of the computation for the vectorVector computation mode.
sigma

0

The coefficient σ of the RBF kernel.

Algorithm Output

The RBF kernel calculates the results described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.

Result ID

Result

values

Pointer to the n x m numeric table with the values of the kernel function. By default, this result is an object of the HomogenNumericTable class, but you can define the result as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

Examples

C++:

Java*: