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Classes
LeavePOut

LeavePOut

Leave-P-Out cross-validator

Provides train/test indices to split data in train/test sets. This results in testing on all distinct samples of size p, while the remaining n - p samples form the training set in each iteration.

Note: LeavePOut(p) is NOT equivalent to KFold(n\_splits=n\_samples // p) which creates non-overlapping test sets.

Due to the high number of iterations which grows combinatorically with the number of samples this cross-validation method can be very costly. For large datasets one should favor KFold, StratifiedKFold or ShuffleSplit.

Read more in the User Guide.

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new LeavePOut(opts?: object): LeavePOut;

Parameters

NameTypeDescription
opts?object-
opts.p?numberSize of the test sets. Must be strictly less than the number of samples.

Returns

LeavePOut

Defined in: generated/model_selection/LeavePOut.ts:29 (opens in a new tab)

Properties

_isDisposed

boolean = false

Defined in: generated/model_selection/LeavePOut.ts:27 (opens in a new tab)

_isInitialized

boolean = false

Defined in: generated/model_selection/LeavePOut.ts:26 (opens in a new tab)

_py

PythonBridge

Defined in: generated/model_selection/LeavePOut.ts:25 (opens in a new tab)

id

string

Defined in: generated/model_selection/LeavePOut.ts:22 (opens in a new tab)

opts

any

Defined in: generated/model_selection/LeavePOut.ts:23 (opens in a new tab)

Accessors

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/model_selection/LeavePOut.ts:39 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/model_selection/LeavePOut.ts:43 (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/LeavePOut.ts:89 (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<any>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Training data, where n\_samples is the number of samples and n\_features is the number of features.
opts.groups?anyAlways ignored, exists for compatibility.
opts.y?anyAlways ignored, exists for compatibility.

Returns

Promise<any>

Defined in: generated/model_selection/LeavePOut.ts:106 (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

NameType
pyPythonBridge

Returns

Promise<void>

Defined in: generated/model_selection/LeavePOut.ts:52 (opens in a new tab)

split()

Generate indices to split data into training and test set.

Signature

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

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Training data, where n\_samples is the number of samples and n\_features is the number of features.
opts.groups?ArrayLikeGroup labels for the samples used while splitting the dataset into train/test set.
opts.y?ArrayLikeThe target variable for supervised learning problems.

Returns

Promise<ArrayLike>

Defined in: generated/model_selection/LeavePOut.ts:151 (opens in a new tab)