Class ISODATA

constructor

• new ISODATA(
      init_k: number,
      min_k: number,
      max_k: number,
      min_n: number,
      split_std: number,
      merge_dist: number,
  ): ISODATA

• Parameters

  • init_k: number

    Initial cluster count
  • min_k: number

    Minimum cluster count
  • max_k: number

    Maximum cluster count
  • min_n: number

    Minimum cluster size
  • split_std: number

    Standard deviation as splid threshold
  • merge_dist: number

    Merge distance

  Returns ISODATA

_centroids

_init_k

_max_k

_merge_distance

_min_k

_min_n

_split_sd

centroids

• get centroids(): number[][]

• Centroids

  Returns number[][]

size

• get size(): number

• Number of clusters

  Returns number

_delete_centroids

• _delete_centroids(datas: any): void

• Parameters

  • datas: any

  Returns void

_distance

• _distance(a: any, b: any): number

• Parameters

  • a: any
  • b: any

  Returns number

_fit_centers

• _fit_centers(data: any): void

• Parameters

  • data: any

  Returns void

_merge_centroids

• _merge_centroids(datas: any): void

• Parameters

  • datas: any

  Returns void

_split_centroids

• _split_centroids(datas: any): void

• Parameters

  • datas: any

  Returns void

fit

• fit(data: number[][]): void

• Fit model.

  Parameters

  • data: number[][]

    Training data

  Returns void

init

• init(data: number[][]): void

• Initialize model.

  Parameters

  • data: number[][]

    Training data

  Returns void

predict

• predict(datas: number[][]): number[]

• Returns predicted categories.

  Parameters

  • datas: number[][]

    Sample data

  Returns number[]

  Predicted values