# Radial Basis Function (RBF) kernel#

The Radial Basis Function (RBF) kernel is a popular kernel function used in kernelized learning algorithms.

 Operation Computational methods Programming Interface dense dense compute(…) compute_input compute_result

## Programming Interface#

All types and functions in this section are declared in the oneapi::dal::rbf_kernel namespace and are available via inclusion of the oneapi/dal/algo/rbf_kernel.hpp header file.

### Descriptor#

template<typename Float = float, typename Method = method::by_default, typename Task = task::by_default>
class descriptor#
Template Parameters
• Float – The floating-point type that the algorithm uses for intermediate computations. Can be float or double.

• Method – Tag-type that specifies an implementation of algorithm. Can be method::dense.

• Task – Tag-type that specifies the type of the problem to solve. Can be task::compute.

Constructors

descriptor() = default#

Creates a new instance of the class with the default property values.

Properties

double sigma#

The coefficient $$\sigma$$ of the RBF kernel. Default value: 1.0.

Getter & Setter
double get_sigma() const
auto & set_sigma(double value)

#### Method tags#

struct dense#
using by_default = dense#

struct compute#

Tag-type that parameterizes entities that are used to compute statistics, distance, and so on.

using by_default = compute#

Alias tag-type for the dense method.

### Training compute(...)#

#### Input#

class compute_input#
Template Parameters

Task – Tag-type that specifies the type of the problem to solve. Can be task::compute.

Constructors

compute_input(const table &x, const table &y)#

Creates a new instance of the class with the given x and y.

Properties

const table &x#

An $$n \times p$$ table with the data x, where each row stores one feature vector. Default value: table{}.

Getter & Setter
const table & get_x() const
auto & set_x(const table &data)
const table &y#

An $$m \times p$$ table with the data y, where each row stores one feature vector. Default value: table{}.

Getter & Setter
const table & get_y() const
auto & set_y(const table &data)

#### Result#

class compute_result#
Template Parameters

Task – Tag-type that specifies the type of the problem to solve. Can be task::compute.

Constructors

compute_result()#

Creates a new instance of the class with the default property values.

Properties

const table &values#

A $$n \times m$$ table with the result kernel functions. Default value: table{}.

Getter & Setter
const table & get_values() const
auto & set_values(const table &value)

#### Operation#

template<typename Descriptor>
rbf_kernel::compute_result compute(const Descriptor &desc, const rbf_kernel::compute_input &input)#
Parameters
• desc – RBF Kernel algorithm descriptor rbf_kernel::descriptor.

• input – Input data for the computing operation

Preconditions
input.data.is_empty == false