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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

Constructors

constructor()

Signature

new RepeatedStratifiedKFold(opts?: object): RepeatedStratifiedKFold;

Parameters

Name Type Description
opts? object -
opts.n_repeats? number Number of times cross-validator needs to be repeated. Default Value 10
opts.n_splits? number Number of folds. Must be at least 2. Default Value 5
opts.random_state? number Controls 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

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

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/RepeatedStratifiedKFold.ts:127

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. np.zeros(n\_samples) may be used as a placeholder.
opts.groups? ArrayLike Group labels for the samples used while splitting the dataset into train/test set.
opts.y? any Always 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

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/RepeatedStratifiedKFold.ts:62

split()

Generates 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.

Returns

Promise<ArrayLike>

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:214

Properties

_isDisposed

boolean = false

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:23

_isInitialized

boolean = false

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:22

_py

PythonBridge

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:21

id

string

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:18

opts

any

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:19

Accessors

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:49

Signature

py(pythonBridge: PythonBridge): void;

Parameters

Name Type
pythonBridge PythonBridge

Returns

void

Defined in: generated/model_selection/RepeatedStratifiedKFold.ts:53