FunctionTransformer
Constructs a transformer from an arbitrary callable.
A FunctionTransformer forwards its X (and optionally y) arguments to a user-defined function or function object and returns the result of this function. This is useful for stateless transformations such as taking the log of frequencies, doing custom scaling, etc.
Note: If a lambda is used as the function, then the resulting transformer will not be pickleable.
Python Reference (opens in a new tab)
Constructors
constructor()
Signature
new FunctionTransformer(opts?: object): FunctionTransformer;Parameters
| Name | Type | Description |
|---|---|---|
opts? | object | - |
opts.accept_sparse? | boolean | Indicate that func accepts a sparse matrix as input. If validate is false, this has no effect. Otherwise, if accept_sparse is false, sparse matrix inputs will cause an exception to be raised. Default Value false |
opts.check_inverse? | boolean | Whether to check that or func followed by inverse\_func leads to the original inputs. It can be used for a sanity check, raising a warning when the condition is not fulfilled. Default Value true |
opts.feature_names_out? | "one-to-one" | Determines the list of feature names that will be returned by the get\_feature\_names\_out method. If it is ‘one-to-one’, then the output feature names will be equal to the input feature names. If it is a callable, then it must take two positional arguments: this FunctionTransformer (self) and an array-like of input feature names (input\_features). It must return an array-like of output feature names. The get\_feature\_names\_out method is only defined if feature\_names\_out is not undefined. See get\_feature\_names\_out for more details. |
opts.func? | any | The callable to use for the transformation. This will be passed the same arguments as transform, with args and kwargs forwarded. If func is undefined, then func will be the identity function. |
opts.inv_kw_args? | any | Dictionary of additional keyword arguments to pass to inverse_func. |
opts.inverse_func? | any | The callable to use for the inverse transformation. This will be passed the same arguments as inverse transform, with args and kwargs forwarded. If inverse_func is undefined, then inverse_func will be the identity function. |
opts.kw_args? | any | Dictionary of additional keyword arguments to pass to func. |
opts.validate? | boolean | Indicate that the input X array should be checked before calling func. The possibilities are: Default Value false |
Returns
Defined in: generated/preprocessing/FunctionTransformer.ts:25 (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/preprocessing/FunctionTransformer.ts:145 (opens in a new tab)
fit()
Fit transformer by checking X.
If validate is true, X will be checked.
Signature
fit(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Input array. |
opts.y? | any | Not used, present here for API consistency by convention. |
Returns
Promise<any>
Defined in: generated/preprocessing/FunctionTransformer.ts:164 (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/preprocessing/FunctionTransformer.ts:206 (opens in a new tab)
get_feature_names_out()
Get output feature names for transformation.
This method is only defined if feature\_names\_out is not undefined.
Signature
get_feature_names_out(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.input_features? | any | Input feature names. |
Returns
Promise<any>
Defined in: generated/preprocessing/FunctionTransformer.ts:259 (opens in a new tab)
get_metadata_routing()
Get metadata routing of this object.
Please check User Guide on how the routing mechanism works.
Signature
get_metadata_routing(opts: object): Promise<any>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.routing? | any | A MetadataRequest encapsulating routing information. |
Returns
Promise<any>
Defined in: generated/preprocessing/FunctionTransformer.ts:299 (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/preprocessing/FunctionTransformer.ts:91 (opens in a new tab)
inverse_transform()
Transform X using the inverse function.
Signature
inverse_transform(opts: object): Promise<ArrayLike>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Input array. |
Returns
Promise<ArrayLike>
Defined in: generated/preprocessing/FunctionTransformer.ts:337 (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/preprocessing/FunctionTransformer.ts:377 (opens in a new tab)
transform()
Transform X using the forward function.
Signature
transform(opts: object): Promise<ArrayLike>;Parameters
| Name | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Input array. |
Returns
Promise<ArrayLike>
Defined in: generated/preprocessing/FunctionTransformer.ts:414 (opens in a new tab)
Properties
_isDisposed
boolean=false
Defined in: generated/preprocessing/FunctionTransformer.ts:23 (opens in a new tab)
_isInitialized
boolean=false
Defined in: generated/preprocessing/FunctionTransformer.ts:22 (opens in a new tab)
_py
PythonBridge
Defined in: generated/preprocessing/FunctionTransformer.ts:21 (opens in a new tab)
id
string
Defined in: generated/preprocessing/FunctionTransformer.ts:18 (opens in a new tab)
opts
any
Defined in: generated/preprocessing/FunctionTransformer.ts:19 (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/preprocessing/FunctionTransformer.ts:476 (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/preprocessing/FunctionTransformer.ts:449 (opens in a new tab)
py
Signature
py(): PythonBridge;Returns
PythonBridge
Defined in: generated/preprocessing/FunctionTransformer.ts:78 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;Parameters
| Name | Type |
|---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/preprocessing/FunctionTransformer.ts:82 (opens in a new tab)