Class RuLSIF

constructor

• new RuLSIF(
      sigma: number[],
      lambda: number[],
      alpha: number,
      kernelNum: number,
  ): RuLSIF

  Parameters

  • sigma: number[]

    Sigmas of normal distribution
  • lambda: number[]

    Regularization parameters
  • alpha: number

    Relative parameter
  • kernelNum: number

    Number of kernels

  Returns RuLSIF

_alpha

_centers

_kernelNum

_kw

_lambda

_lambda_cand

_sigma

_sigma_cand

_kernel_gaussian

• _kernel_gaussian(x: any, c: any, s: any): Matrix<number[]>

  Parameters

  • x: any
  • c: any
  • s: any

  Returns Matrix<number[]>

fit

• fit(x1: number[][], x2: number[][]): void

  Fit model.

  Parameters

  • x1: number[][]

    Numerator data
  • x2: number[][]

    Denominator data

  Returns void

predict

• predict(x: number[][]): number[]

  Returns estimated values.

  Parameters

  • x: number[][]

    Sample data

  Returns number[]

  Predicted values