StratifiedKFold.md

StratifiedKFold

Stratified K-Folds cross-validator.

Provides train/test indices to split data in train/test sets.

This cross-validation object is a variation of KFold that returns stratified folds. The folds are made by preserving the percentage of samples for each class.

Read more in the User Guide.

For visualisation of cross-validation behaviour and comparison between common scikit-learn split methods refer to Visualizing cross-validation behavior in scikit-learn

Python Reference

Constructors

constructor()

Signature

new StratifiedKFold(opts?: object): StratifiedKFold;

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 for each class. Otherwise, leave random\_state as undefined. Pass an int for reproducible output across multiple function calls. See Glossary.
opts.shuffle?	boolean	Whether to shuffle each class’s samples before splitting into batches. Note that the samples within each split will not be shuffled. Default Value false

Returns

StratifiedKFold

Defined in: generated/model_selection/StratifiedKFold.ts:29

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/StratifiedKFold.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/StratifiedKFold.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.
opts.groups?	any	Always ignored, exists for compatibility.
opts.y?	any	Always ignored, exists for compatibility.

Returns

Promise<number>

Defined in: generated/model_selection/StratifiedKFold.ts:162

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/StratifiedKFold.ts:66

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. Note that providing y is sufficient to generate the splits and hence np.zeros(n\_samples) may be used as a placeholder for X instead of actual training data.
opts.groups?	any	Always ignored, exists for compatibility.
opts.y?	ArrayLike	The target variable for supervised learning problems. Stratification is done based on the y labels.

Returns

Promise<ArrayLike>

Defined in: generated/model_selection/StratifiedKFold.ts:205

Properties

_isDisposed

boolean = false

Defined in: generated/model_selection/StratifiedKFold.ts:27

_isInitialized

boolean = false

Defined in: generated/model_selection/StratifiedKFold.ts:26

_py

PythonBridge

Defined in: generated/model_selection/StratifiedKFold.ts:25

id

string

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

opts

any

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

Accessors

py

Signature

py(): PythonBridge;

Returns

PythonBridge

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

Signature

py(pythonBridge: PythonBridge): void;

Parameters

Name	Type
pythonBridge	PythonBridge

Returns

void

Defined in: generated/model_selection/StratifiedKFold.ts:57