Multiclass Budgeted Stochastic Gradient Descent

Constructors

  • Parameters

    • Optionalb: number

      Budget size

    • Optionaleta: number

      Learning rate

    • Optionallambda: number

      Regularization parameter

    • Optionalmaintenance: "removal" | "projection" | "merging"

      Maintenance type

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

      Kernel name

    Returns MulticlassBSGD

Properties

_alpha: any[]
_b: number
_classes: any[]
_eta: number
_kernel: any
_lambda: number
_maintenance: "removal" | "projection" | "merging"
_sv: any[]

Methods

  • Fit model.

    Parameters

    • x: number[][]

      Training data

    • y: any[]

      Target values

    Returns void

  • Returns predicted values.

    Parameters

    • data: number[][]

      Sample data

    Returns any[]

    Predicted values