semi-supervised k-means model

Hierarchy

  • KMeansBase
    • SemiSupervisedKMeansModel

Constructors

Properties

_centroids: any[]
_classes: any[]

Accessors

  • get categories(): any[]
  • Categories

    Returns any[]

  • get centroids(): number[][]
  • Centroids

    Returns number[][]

  • get size(): number
  • Number of clusters.

    Returns number

Methods

  • Parameters

    • a: any
    • b: any

    Returns number

  • Parameters

    • d: any

    Returns number[]

  • Add a new cluster.

    Returns void

    Added centroid

  • Clear all clusters.

    Returns void

  • Fit and returns total distance the centroid has moved.

    Parameters

    • datas: number[][]

      Training data

    • labels: any[]

      Target values

    Returns number

    Total distance the centroid has moved

  • Initialize model.

    Parameters

    • datas: number[][]

      Training data

    • labels: any[]

      Target values

    Returns void

  • Returns predicted categories.

    Parameters

    • datas: number[][]

      Sample data

    Returns any[]

    Predicted values