KMeansDistanceMetric

Provides constants for different distance metrics for the kMeansClustering.

Constants

: number

Specifies the Chebyshev distance metric or L_∞ metric.

This is calculated by max(p1.x - p2.x) + abs(p1.y - p2.y)

: number

Specifies the (squared) Euclidean distance metric or L² metric.

This is calculated by (p1.x - p2.x)^2 + (p1.y - p2.y)^2.

: number

Specifies the Manhattan distance metric or L¹ metric.

This is calculated by abs(p1.x - p2.x) + abs(p1.y - p2.y)

Converts the given argument to an enum constant of this enum type.

Most notably, this method can convert an enum constant's name into the enum constant itself.

options - Object
A map of options to pass to the method.

↪KMeansDistanceMetric: The enum constant that corresponds to the given argument.

Returns the name of the given enum constant.

options - Object
A map of options to pass to the method.

Exception({ name: 'Error' }): If this type is a flags enums, and the provided value doesn't correspond to a single enum constant, or if this enum type contains no constant of the given numeric value.