Radial basis function kernel (aka squared-exponential kernel).
The RBF kernel is a stationary kernel. It is also known as the “squared exponential” kernel. It is parameterized by a length scale parameter \(l>0\), which can either be a scalar (isotropic variant of the kernel) or a vector with the same number of dimensions as the inputs X (anisotropic variant of the kernel). The kernel is given by:
new RBF(opts?: object): RBF;
Name | Type | Description |
---|---|---|
opts? |
object |
- |
opts.length_scale? |
number | ArrayLike |
The length scale of the kernel. If a float, an isotropic kernel is used. If an array, an anisotropic kernel is used where each dimension of l defines the length-scale of the respective feature dimension. Default Value 1 |
opts.length_scale_bounds? |
"fixed" |
The lower and upper bound on ‘length_scale’. If set to “fixed”, ‘length_scale’ cannot be changed during hyperparameter tuning. |
Defined in: generated/gaussian_process/kernels/RBF.ts:23
Return the kernel k(X, Y) and optionally its gradient.
__call__(opts: object): Promise<ArrayLike[]>;
Name | Type | Description |
---|---|---|
opts |
object |
- |
opts.X? |
ArrayLike [] |
Left argument of the returned kernel k(X, Y) |
opts.Y? |
ArrayLike [] |
Right argument of the returned kernel k(X, Y). If undefined , k(X, X) if evaluated instead. |
opts.eval_gradient? |
boolean |
Determines whether the gradient with respect to the log of the kernel hyperparameter is computed. Only supported when Y is undefined . Default Value false |
Promise
<ArrayLike
[]>
Defined in: generated/gaussian_process/kernels/RBF.ts:113
Returns a clone of self with given hyperparameters theta.
clone_with_theta(opts: object): Promise<any>;
Name | Type | Description |
---|---|---|
opts |
object |
- |
opts.theta? |
ArrayLike |
The hyperparameters |
Promise
<any
>
Defined in: generated/gaussian_process/kernels/RBF.ts:162
Returns the diagonal of the kernel k(X, X).
The result of this method is identical to np.diag(self(X)); however, it can be evaluated more efficiently since only the diagonal is evaluated.
diag(opts: object): Promise<ArrayLike>;
Name | Type | Description |
---|---|---|
opts |
object |
- |
opts.X? |
ArrayLike [] |
Left argument of the returned kernel k(X, Y) |
Promise
<ArrayLike
>
Defined in: generated/gaussian_process/kernels/RBF.ts:197
Disposes of the underlying Python resources.
Once dispose()
is called, the instance is no longer usable.
dispose(): Promise<void>;
Promise
<void
>
Defined in: generated/gaussian_process/kernels/RBF.ts:96
Initializes the underlying Python resources.
This instance is not usable until the Promise
returned by init()
resolves.
init(py: PythonBridge): Promise<void>;
Name | Type |
---|---|
py |
PythonBridge |
Promise
<void
>
Defined in: generated/gaussian_process/kernels/RBF.ts:53
Returns whether the kernel is stationary.
is_stationary(opts: object): Promise<any>;
Name | Type |
---|---|
opts |
object |
Promise
<any
>
Defined in: generated/gaussian_process/kernels/RBF.ts:229
boolean
=false
Defined in: generated/gaussian_process/kernels/RBF.ts:21
boolean
=false
Defined in: generated/gaussian_process/kernels/RBF.ts:20
PythonBridge
Defined in: generated/gaussian_process/kernels/RBF.ts:19
string
Defined in: generated/gaussian_process/kernels/RBF.ts:16
any
Defined in: generated/gaussian_process/kernels/RBF.ts:17
anisotropic(): Promise<any>;
Promise
<any
>
Defined in: generated/gaussian_process/kernels/RBF.ts:252
hyperparameter_length_scale(): Promise<any>;
Promise
<any
>
Defined in: generated/gaussian_process/kernels/RBF.ts:272
py(): PythonBridge;
PythonBridge
Defined in: generated/gaussian_process/kernels/RBF.ts:40
py(pythonBridge: PythonBridge): void;
Name | Type |
---|---|
pythonBridge |
PythonBridge |
void
Defined in: generated/gaussian_process/kernels/RBF.ts:44