TimeSeriesSplit

Time Series cross-validator

Provides train/test indices to split time series data samples that are observed at fixed time intervals, in train/test sets. In each split, test indices must be higher than before, and thus shuffling in cross validator is inappropriate.

This cross-validation object is a variation of KFold. In the kth split, it returns first k folds as train set and the (k+1)th fold as test set.

Note that unlike standard cross-validation methods, successive training sets are supersets of those that come before them.

Constructors

constructor()

Signature

new TimeSeriesSplit(opts?: object): TimeSeriesSplit;

Parameters

Name	Type	Description
`opts?`	`object`	-
`opts.gap?`	`number`	Number of samples to exclude from the end of each train set before the test set. `Default Value` `0`
`opts.max_train_size?`	`number`	Maximum size for a single training set.
`opts.n_splits?`	`number`	Number of splits. Must be at least 2. `Default Value` `5`
`opts.test_size?`	`number`	Used to limit the size of the test set. Defaults to `n\_samples // (n\_splits + 1)`, which is the maximum allowed value with `gap=0`.

Returns

TimeSeriesSplit

Defined in: generated/model_selection/TimeSeriesSplit.ts:31 (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/TimeSeriesSplit.ts:117 (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/TimeSeriesSplit.ts:136 (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/TimeSeriesSplit.ts:171 (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/TimeSeriesSplit.ts:73 (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`	Always ignored, exists for compatibility.
`opts.y?`	`ArrayLike`	Always ignored, exists for compatibility.