Kernelized Primal Estimated sub-GrAdientSOlver for SVM

Constructors

Properties

Methods

Constructors

  • Parameters

    • rate: number

      Learning rate

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

      Kernel name

    Returns KernelizedPegasos

Properties

_a: any[]
_itr: number
_k: any[]
_kernel: any
_r: number
_t: number
_x: number[][]
_y: (-1 | 1)[]

Methods

  • Fit model parameters.

    Returns void

  • Initialize this model.

    Parameters

    • train_x: number[][]

      Training data

    • train_y: (-1 | 1)[]

      Target values

    Returns void

  • Returns predicted values.

    Parameters

    • data: number[][]

      Sample data

    Returns (-1 | 1)[]

    Predicted values