Class TightestPerceptron

constructor

• new TightestPerceptron(
      b?: number,
      kernel?:
          | "gaussian"
          | "polynomial"
          | { name: "gaussian"; s?: number }
          | { d?: number; name: "polynomial" }
          | ((arg0: number[], arg1: number[]) => number),
      accuracyLoss?: "zero_one" | "hinge",
  ): TightestPerceptron

  Parameters

  • Optionalb: number

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

    Kernel name
  • OptionalaccuracyLoss: "zero_one" | "hinge"

    Accuracy loss type name

  Returns TightestPerceptron

_accuracyLossN

_accuracyLossP

_an

_ap

_b

_kernel

_sv

_updateSummary

• _updateSummary(x: any, cp: any, cn: any): void

  Parameters

  • x: any
  • cp: any
  • cn: any

  Returns void

fit

• fit(x: number[][], y: (-1 | 1)[]): void

  Fit model parameters.

  Parameters

  • x: number[][]

    Training data
  • y: (-1 | 1)[]

    Target values

  Returns void

predict

• predict(data: number[][]): (-1 | 1)[]

  Returns predicted values.

  Parameters

  • data: number[][]

    Sample data

  Returns (-1 | 1)[]

  Predicted values