Class ADAMENN

constructor

• new ADAMENN(
      k0?: number,
      k1?: number,
      k2?: number,
      l?: number,
      k?: number,
      c?: number,
  ): ADAMENN

  Parameters

  • Optionalk0: number

    The number of neighbors of the test point

  • Optionalk1: number

    The number of neighbors in N1 for estimation

  • Optionalk2: number

    The size of the neighborhood N2 for each of the k0 neighbors for estimation

  • Optionall: number

    The number of points within the delta intervals

  • Optionalk: number

    The number of neighbors in the final nearest neighbor rule

  • Optionalc: number

    The positive factor for the exponential weighting scheme

  Returns ADAMENN

_c

_classes

_itr

_k

_k0

_k1

_k2

_l

_x

_y

_d

• _d(a: any, b: any, w: any): number

  Parameters

  • a: any
  • b: any
  • w: any

  Returns number

fit

• fit(x: number[][], y: any[]): void

  Fit model.

  Parameters

  • x: number[][]

    Training data

  • y: any[]

    Target values

  Returns void

predict

• predict(datas: number[][]): any[]

  Returns predicted categories.

  Parameters

  • datas: number[][]

    Sample data

  Returns any[]

  Predicted values