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.
Python Reference (opens in a new tab)
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
Defined in: generated/model_selection/StratifiedKFold.ts:27 (opens in a new tab)
Properties
_isDisposed
boolean=false
Defined in: generated/model_selection/StratifiedKFold.ts:25 (opens in a new tab)
_isInitialized
boolean=false
Defined in: generated/model_selection/StratifiedKFold.ts:24 (opens in a new tab)
_py
PythonBridge
Defined in: generated/model_selection/StratifiedKFold.ts:23 (opens in a new tab)
id
string
Defined in: generated/model_selection/StratifiedKFold.ts:20 (opens in a new tab)
opts
any
Defined in: generated/model_selection/StratifiedKFold.ts:21 (opens in a new tab)
Accessors
py
Signature
py(): PythonBridge;Returns
PythonBridge
Defined in: generated/model_selection/StratifiedKFold.ts:51 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;Parameters
| Name | Type |
|---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/model_selection/StratifiedKFold.ts:55 (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/StratifiedKFold.ts:106 (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/StratifiedKFold.ts:123 (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/StratifiedKFold.ts:64 (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. 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:166 (opens in a new tab)