DistanceMetric

Provides constants for different metrics used in KMeansClustering and kMeansClustering.

Constants

: number

Specifies the Chebychev distance metric or L_∞ metric.

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

: number

Specifies the euclidean distance metric or L² metric.

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

When this value is set to the metric property, it has the same effect as the EUCLIDEAN_SQUARED value.

: number

Specifies the (squared) euclidean distance metric.

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

When this value is set to the metric property, it has the same effect as the EUCLIDEAN value.

: 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 argument to DistanceMetric.

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

↪DistanceMetric: Either value if it is already a DistanceMetric or an appropriate converted value.