AdditiveChi2Sampler
Approximate feature map for additive chi2 kernel.
Uses sampling the fourier transform of the kernel characteristic at regular intervals.
Since the kernel that is to be approximated is additive, the components of the input vectors can be treated separately. Each entry in the original space is transformed into 2*sample_steps-1 features, where sample_steps is a parameter of the method. Typical values of sample_steps include 1, 2 and 3.
Optimal choices for the sampling interval for certain data ranges can be computed (see the reference). The default values should be reasonable.
Read more in the User Guide.
Python Reference (opens in a new tab)
Constructors
constructor()
Signature
new AdditiveChi2Sampler(opts?: object): AdditiveChi2Sampler;Parameters
| Name | Type | Description |
|---|---|---|
opts? | object | - |
opts.sample_interval? | number | Sampling interval. Must be specified when sample_steps not in {1,2,3}. |
opts.sample_steps? | number | Gives the number of (complex) sampling points. Default Value 2 |
Returns
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:29 (opens in a new tab)
Properties
_isDisposed
boolean=false
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:27 (opens in a new tab)
_isInitialized
boolean=false
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:26 (opens in a new tab)
_py
PythonBridge
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:25 (opens in a new tab)
id
string
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:22 (opens in a new tab)
opts
any
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:23 (opens in a new tab)
Accessors
feature_names_in_
Names of features seen during fit. Defined only when X has feature names that are all strings.
Signature
feature_names_in_(): Promise<ArrayLike>;Returns
Promise<ArrayLike>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:379 (opens in a new tab)
n_features_in_
Number of features seen during fit.
Signature
n_features_in_(): Promise<number>;Returns
Promise<number>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:352 (opens in a new tab)
py
Signature
py(): PythonBridge;Returns
PythonBridge
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:46 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;Parameters
| Name | Type |
|---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:50 (opens in a new tab)
sample_interval_
Stored sampling interval. Specified as a parameter if sample\_steps not in {1,2,3}.
Signature
sample_interval_(): Promise<number>;Returns
Promise<number>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:325 (opens in a new tab)
Methods
dispose()
Disposes of the underlying Python resources.
Once dispose() is called, the instance is no longer usable.
Signature
dispose(): Promise<void>;Returns
Promise<void>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:103 (opens in a new tab)
fit()
Set the parameters.
Signature
fit(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | ArrayLike | Training data, where n\_samples is the number of samples and n\_features is the number of features. |
opts.y? | ArrayLike | Target values (undefined for unsupervised transformations). |
Returns
Promise<any>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:120 (opens in a new tab)
fit_transform()
Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit\_params and returns a transformed version of X.
Signature
fit_transform(opts: object): Promise<any[]>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | ArrayLike[] | Input samples. |
opts.fit_params? | any | Additional fit parameters. |
opts.y? | ArrayLike | Target values (undefined for unsupervised transformations). |
Returns
Promise<any[]>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:162 (opens in a new tab)
get_feature_names_out()
Get output feature names for transformation.
Signature
get_feature_names_out(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.input_features? | any | Only used to validate feature names with the names seen in fit. |
Returns
Promise<any>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:213 (opens in a new tab)
init()
Initializes the underlying Python resources.
This instance is not usable until the Promise returned by init() resolves.
Signature
init(py: PythonBridge): Promise<void>;Parameters
| Name | Type |
|---|---|
py | PythonBridge |
Returns
Promise<void>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:59 (opens in a new tab)
set_output()
Set output container.
See Introducing the set_output API for an example on how to use the API.
Signature
set_output(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.transform? | "default" | "pandas" | Configure output of transform and fit\_transform. |
Returns
Promise<any>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:253 (opens in a new tab)
transform()
Apply approximate feature map to X.
Signature
transform(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Training data, where n\_samples is the number of samples and n\_features is the number of features. |
Returns
Promise<any>
Defined in: generated/kernel_approximation/AdditiveChi2Sampler.ts:290 (opens in a new tab)