Class: LeavePGroupsOut
Leave P Group(s) Out cross-validator.
Provides train/test indices to split data according to a third-party provided group. This group information can be used to encode arbitrary domain specific stratifications of the samples as integers.
For instance the groups could be the year of collection of the samples and thus allow for cross-validation against time-based splits.
The difference between LeavePGroupsOut and LeaveOneGroupOut is that the former builds the test sets with all the samples assigned to p different values of the groups while the latter uses samples all assigned the same groups.
Read more in the User Guide.
Constructors
new LeavePGroupsOut()
new LeavePGroupsOut(
opts?):LeavePGroupsOut
Parameters
| Parameter | Type | Description |
|---|---|---|
opts? | object | - |
opts.n_groups? | number | Number of groups (p) to leave out in the test split. |
Returns LeavePGroupsOut
Defined in generated/model_selection/LeavePGroupsOut.ts:29
Properties
| Property | Type | Default value | Defined in |
|---|---|---|---|
_isDisposed | boolean | false | generated/model_selection/LeavePGroupsOut.ts:27 |
_isInitialized | boolean | false | generated/model_selection/LeavePGroupsOut.ts:26 |
_py | PythonBridge | undefined | generated/model_selection/LeavePGroupsOut.ts:25 |
id | string | undefined | generated/model_selection/LeavePGroupsOut.ts:22 |
opts | any | undefined | generated/model_selection/LeavePGroupsOut.ts:23 |
Accessors
py
Get Signature
get py():
PythonBridge
Returns PythonBridge
Set Signature
set py(
pythonBridge):void
Parameters
| Parameter | Type |
|---|---|
pythonBridge | PythonBridge |
Returns void
Defined in generated/model_selection/LeavePGroupsOut.ts:39
Methods
dispose()
dispose():
Promise<void>
Disposes of the underlying Python resources.
Once dispose() is called, the instance is no longer usable.
Returns Promise<void>
Defined in generated/model_selection/LeavePGroupsOut.ts:91
get_metadata_routing()
get_metadata_routing(
opts):Promise<any>
Get metadata routing of this object.
Please check User Guide on how the routing mechanism works.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.routing? | any | A MetadataRequest encapsulating routing information. |
Returns Promise<any>
Defined in generated/model_selection/LeavePGroupsOut.ts:110
get_n_splits()
get_n_splits(
opts):Promise<number>
Returns the number of splitting iterations in the cross-validator.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.groups? | ArrayLike | Group labels for the samples used while splitting the dataset into train/test set. This ‘groups’ parameter must always be specified to calculate the number of splits, though the other parameters can be omitted. |
opts.X? | any | Always ignored, exists for compatibility. |
opts.y? | any | Always ignored, exists for compatibility. |
Returns Promise<number>
Defined in generated/model_selection/LeavePGroupsOut.ts:144
init()
init(
py):Promise<void>
Initializes the underlying Python resources.
This instance is not usable until the Promise returned by init() resolves.
Parameters
| Parameter | Type |
|---|---|
py | PythonBridge |
Returns Promise<void>
Defined in generated/model_selection/LeavePGroupsOut.ts:52
set_split_request()
set_split_request(
opts):Promise<any>
Request metadata passed to the split method.
Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config). Please see User Guide on how the routing mechanism works.
The options for each parameter are:
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.groups? | string | boolean | Metadata routing for groups parameter in split. |
Returns Promise<any>
Defined in generated/model_selection/LeavePGroupsOut.ts:190
split()
split(
opts):Promise<ArrayLike>
Generate indices to split data into training and test set.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.groups? | ArrayLike | Group labels for the samples used while splitting the dataset into train/test set. |
opts.X? | ArrayLike[] | Training data, where n_samples is the number of samples and n_features is the number of features. |
opts.y? | ArrayLike | The target variable for supervised learning problems. |
Returns Promise<ArrayLike>