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Classes
RepeatedStratifiedKFold

RepeatedStratifiedKFold

Repeated Stratified K-Fold cross validator.

Repeats Stratified K-Fold n times with different randomization in each repetition.

Read more in the User Guide.

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new RepeatedStratifiedKFold(opts?: object): RepeatedStratifiedKFold;

Parameters

NameTypeDescription
opts?object-
opts.n_repeats?numberNumber of times cross-validator needs to be repeated. Default Value 10
opts.n_splits?numberNumber of folds. Must be at least 2. Default Value 5
opts.random_state?numberControls the generation of the random states for each repetition. Pass an int for reproducible output across multiple function calls. See Glossary.

Returns

RepeatedStratifiedKFold

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:25 (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/RepeatedStratifiedKFold.ts:108 (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

NameTypeDescription
optsobject-
opts.routing?anyA MetadataRequest encapsulating routing information.

Returns

Promise<any>

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:127 (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

NameTypeDescription
optsobject-
opts.X?anyAlways ignored, exists for compatibility. np.zeros(n\_samples) may be used as a placeholder.
opts.groups?ArrayLikeGroup labels for the samples used while splitting the dataset into train/test set.
opts.y?anyAlways ignored, exists for compatibility. np.zeros(n\_samples) may be used as a placeholder.

Returns

Promise<number>

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:165 (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/RepeatedStratifiedKFold.ts:62 (opens in a new tab)

split()

Generates 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/RepeatedStratifiedKFold.ts:214 (opens in a new tab)

Properties

_isDisposed

boolean = false

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

_isInitialized

boolean = false

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

_py

PythonBridge

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:21 (opens in a new tab)

id

string

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:18 (opens in a new tab)

opts

any

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:19 (opens in a new tab)

Accessors

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:49 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:53 (opens in a new tab)