Mathematical formulation

Programming Interface

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

result_option_id

result_options

Choose which results should be computed and returned.

Getter & Setter

result_option_id get_result_options() const
auto & set_result_options(const result_option_id &value)

struct

dense

Tag-type that denotes dense computational method.

using

by_default

= dense

Alias tag-type for the dense computational method.

struct

compute

Tag-type that parameterizes entities that are used to compute statistics.

using

by_default

= compute

Alias tag-type for the compute task.

template<typename

Task

= task::by_default>

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 &

data

)

Creates a new instance of the class with the given

data

property value.

Properties

const

table &

data

An table with the training data, where each row stores one feature vector.

Default value

: table{}.

Getter & Setter

const table & get_data() const
auto & set_data(const table &value)

template<typename

Task

= task::by_default>

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 &

cor_matrix

The correlation matrix.

Default value

: table{}.

Getter & Setter

const table & get_cor_matrix() const
auto & set_cor_matrix(const table &value)

const

result_option_id &

result_options

Result options that indicates availability of the properties.

Default value

: default_result_options<Task>.

Getter & Setter

const result_option_id & get_result_options() const
auto & set_result_options(const result_option_id &value)

const

table &

means

Means.

Default value

: table{}.

Getter & Setter

const table & get_means() const
auto & set_means(const table &value)

const

table &

cov_matrix

The covariance matrix.

Default value

: table{}.

Getter & Setter

const table & get_cov_matrix() const
auto & set_cov_matrix(const table &value)

template<typename

Descriptor

> covariance::compute_result

compute

(

const

Descriptor &

desc

,

const

covariance::compute_input &

input

)

Parameters

desc
– Covariance algorithm descriptor
covariance::descriptor
input
– Input data for the computing operation

Preconditions

input.data.is_empty == false