Hierarchical Density-based spatial clustering of applications with noise

Constructors

Properties

Accessors

Methods

Constructors

  • Parameters

    • OptionalminClusterSize: number

      Minimum number of clusters to be recognized as a cluster

    • OptionalminPts: number

      Number of neighborhood with core distance

    • Optionalmetric:
          | "euclid"
          | "manhattan"
          | "chebyshev"
          | (arg0: number[], arg1: number[]) => number

      Metric name

    Returns HDBSCAN

Properties

_d: (a: any, b: any) => any
_lastResult: any[]
_metric:
    | "euclid"
    | "manhattan"
    | "chebyshev"
    | (arg0: number[], arg1: number[]) => number
_minClusterSize: number
_minPts: number

Accessors

  • get size(): number
  • Number of clusters of last predicted

    Returns number

Methods

  • Returns predicted categories.

    Parameters

    • datas: number[][]

      Training data

    Returns number[]

    Predicted values