LeaveOneGroupOut

Leave One Group Out cross-validator

Provides train/test indices to split data such that each training set is comprised of all samples except ones belonging to one specific group. Arbitrary domain specific group information is provided an array integers that encodes the group of each sample.

For instance the groups could be the year of collection of the samples and thus allow for cross-validation against time-based splits.

Constructors

constructor()

Signature

new LeaveOneGroupOut(opts?: object): LeaveOneGroupOut;

Parameters

Name	Type	Description
`opts?`	`object`	-
`opts.routing?`	`any`	A `MetadataRequest` encapsulating routing information.

Returns

LeaveOneGroupOut

Defined in: generated/model_selection/LeaveOneGroupOut.ts:27 (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/model_selection/LeaveOneGroupOut.ts:92 (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/model_selection/LeaveOneGroupOut.ts:111 (opens in a new tab)

get_n_splits()

Returns the number of splitting iterations in the cross-validator

Signature

get_n_splits(opts: object): Promise<number>;

Parameters

Name	Type	Description
`opts`	`object`	-
`opts.X?`	`any`	Always ignored, exists for compatibility.
`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.y?`	`any`	Always ignored, exists for compatibility.

Returns

Promise<number>

Defined in: generated/model_selection/LeaveOneGroupOut.ts:148 (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/model_selection/LeaveOneGroupOut.ts:50 (opens in a new tab)

set_split_request()

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:

Signature

set_split_request(opts: object): Promise<any>;

Parameters

Name	Type	Description
`opts`	`object`	-
`opts.groups?`	`string` \| `boolean`	Metadata routing for `groups` parameter in `split`.

Returns

Promise<any>

Defined in: generated/model_selection/LeaveOneGroupOut.ts:199 (opens in a new tab)

split()

Generate indices to split data into training and test set.

Signature

split(opts: object): Promise<ArrayLike>;

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.groups?`	`ArrayLike`	Group labels for the samples used while splitting the dataset into train/test set.
`opts.y?`	`ArrayLike`	The target variable for supervised learning problems.