Minkowski distance¶

The Minkowski distances are the set of distance metrics with different degree \((p > 0)\) and are widely used for distance computation in different algorithms. The most commonly used distance metric, Euclidean distance, is also a Minkowski distance with \(p = 2.0\).

Operation	Computational methods
dense	dense

Mathematical formulation¶

Refer to Developer Guide: Minkowski distance.

Programming Interface¶

All types and functions in this section are declared in the oneapi::dal::minkowski_distance namespace.

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 the implementation of the 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.

descriptor(double degree)¶: Creates a new instance of the class with the external property values.

Properties

double degree¶

The coefficient \(p\) of the Minkowski distance. Default value: 2.0.

Getter & Setter: double get_degree() const

auto & set_degree(double value)

Method tags¶

struct dense¶

using by_default = dense ¶: Alias tag-type for the dense method.

Task tags¶

struct compute¶: Tag-type that parameterizes entities that are used to compute distances.

using by_default = compute ¶: Alias tag-type for the compute task.

Pairwise Distances

Chebyshev distance

oneDAL documentation