@ai-on-browser/data-analysis-models
    Preparing search index...

    Ordering points to identify the clustering structure

    Index

    Constructors

    • Parameters

      • threshold: number

        Threshold

      • Optionaleps: number

        Radius to determine neighborhood

      • OptionalminPts: number

        Number of neighborhood with core distance

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

        Metric name

      Returns OPTICS

    Properties

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

    Methods

    • Fit model.

      Parameters

      • datas: number[][]

        Training data

      Returns void

    • Returns predicted categories.

      Returns number[]

      Predicted values