DBSCAN class

Density-based spatial clustering of applications with noise (DBSCAN)

Constructors

DBSCAN({double epsilon = 1, int minPoints = 2, double distanceMeasure(List<double>, List<double>) = euclideanDistance})

Properties

cluster → List<List<int>>

Result clusters

no setter

dataset ↔ List<List<double>>

Complete list of points (in vector form)

getter/setter pair

distanceMeasure ↔ double Function(List<double>, List<double>)

Distance measurement between two points

getter/setter pair

epsilon → double

Threshold distance for two points to be considered as neighbor

final

hashCode → int

The hash code for this object.

no setter, inherited

label → List<int>?

Cluster label for each points, if prefers sklearn's output structure.

no setter

minPoints → int

Minimum points in neighborhood to be considered as a cluster

final

noise → List<int>

Index of points considered as noise

no setter

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

run(List<List<double>> dataset) → List<List<int>>

Run clustering process, add configs in constructor

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited