Gaussian Process Latent Variable Model

Constructors

  • Parameters

    • rd: number

      Reduced dimension

    • alpha: number

      Precision parameter

    • Optionalez: number

      Learning rate for z

    • Optionalea: number

      Learning rate for alpha

    • Optionalep: number

      Learning rate for kernel

    • Optionalkernel: "gaussian" | { a?: number; b?: number; name: "gaussian" }

      Kernel name

    Returns GPLVM

Properties

_alpha: number
_ea: number
_ez: number
_kernel: GaussianKernel
_rd: number
_s: Matrix
_x: Matrix<number[]>
_z: Matrix

Methods

  • Fit model.

    Returns void

  • Initialize model.

    Parameters

    • x: number[][]

      Training data

    Returns void

  • Returns log likelihood.

    Returns number

    Log likelihood

  • Returns reduced datas.

    Returns number[][]

    Predicted values

  • Returns reconstruct datas.

    Parameters

    • z: number[][]

      Sample data

    Returns number[][]

    Predicted values