KFold

K-Folds cross-validator

Provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).

Each fold is then used once as a validation while the k - 1 remaining folds form the training set.

Constructors

constructor()

Signature

new KFold(opts?: object): KFold;

Parameters

Name	Type	Description
`opts?`	`object`	-
`opts.n_splits?`	`number`	Number of folds. Must be at least 2. `Default Value` `5`
`opts.random_state?`	`number`	When `shuffle` is `true`, `random\_state` affects the ordering of the indices, which controls the randomness of each fold. Otherwise, this parameter has no effect. Pass an int for reproducible output across multiple function calls. See Glossary.
`opts.shuffle?`	`boolean`	Whether to shuffle the data before splitting into batches. Note that the samples within each split will not be shuffled. `Default Value` `false`

Returns

KFold

Defined in: generated/model_selection/KFold.ts:29 (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/KFold.ts:107 (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/KFold.ts:126 (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?`	`any`	Always ignored, exists for compatibility.
`opts.y?`	`any`	Always ignored, exists for compatibility.

Returns

Promise<number>

Defined in: generated/model_selection/KFold.ts:159 (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/KFold.ts:66 (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.