Kernel

Defined in: ds/src/ml/kernels/base.js:13

Abstract base class for GP kernels

Extended by

• RBF
• Periodic
• RationalQuadratic
• ConstantKernel
• SumKernel
• Matern
• DotProduct

Constructors

Constructor

new Kernel(): Kernel

Returns

Kernel

Methods

call()

call(X1, X2?): Matrix

Defined in: ds/src/ml/kernels/base.js:30

Compute covariance matrix between sets of points

Parameters

X1

any

First set of points (n1 x d)

X2?

any = null

Second set of points (n2 x d). If omitted, computes K(X1, X1)

Returns

Matrix

Covariance matrix (n1 x n2)

---

clone()

clone(): Kernel

Defined in: ds/src/ml/kernels/base.js:76

Clone the kernel with the same parameters

Returns

Kernel

New kernel instance

---

compute()

compute(_x1, _x2): number

Defined in: ds/src/ml/kernels/base.js:20

Compute covariance between two points

Parameters

_x1

any

_x2

any

Returns

number

Covariance value

---

getParams()

getParams(): any

Defined in: ds/src/ml/kernels/base.js:60

Get kernel hyperparameters

Returns

any

Hyperparameters

---

setParams()

setParams(_params): void

Defined in: ds/src/ml/kernels/base.js:68

Set kernel hyperparameters

Parameters

_params

any

Returns

void