Class COLL

constructor

• new COLL(
      c: number,
      eta?: number,
      kernel?:
          | "gaussian"
          | "polynomial"
          | { name: "gaussian"; s?: number }
          | { d?: number; name: "polynomial" }
          | ((arg0: number[], arg1: number[]) => number),
  ): COLL

  Parameters

  • c: number

    Number of clusters
  • Optionaleta: number

    Initial learning rate
  • Optionalkernel:
        | "gaussian"
        | "polynomial"
        | { name: "gaussian"; s?: number }
        | { d?: number; name: "polynomial" }
        | ((arg0: number[], arg1: number[]) => number)

    Kernel name

  Returns COLL

_c

_datas

_eta

_f

_k

_kernel

_nk

_nu

_t

_w

fit

• fit(): number

  Fit model once.

  Returns number

  Convergence criterion

init

• init(datas: number[][]): void

  Initialize model.

  Parameters

  • datas: number[][]

    Training data

  Returns void

predict

• predict(): number[]

  Returns predicted categories.

  Returns number[]

  Predicted values