Class: StratifiedKFold
Stratified K-Fold 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
Constructors
new StratifiedKFold()
new StratifiedKFold(
opts?):StratifiedKFold
Parameters
| Parameter | Type | Description |
|---|---|---|
opts? | object | - |
opts.n_splits? | number | Number of folds. Must be at least 2. |
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. |
Returns StratifiedKFold
Defined in generated/model_selection/StratifiedKFold.ts:29
Properties
| Property | Type | Default value | Defined in |
|---|---|---|---|
_isDisposed | boolean | false | generated/model_selection/StratifiedKFold.ts:27 |
_isInitialized | boolean | false | generated/model_selection/StratifiedKFold.ts:26 |
_py | PythonBridge | undefined | generated/model_selection/StratifiedKFold.ts:25 |
id | string | undefined | generated/model_selection/StratifiedKFold.ts:22 |
opts | any | undefined | generated/model_selection/StratifiedKFold.ts:23 |
Accessors
py
Get Signature
get py():
PythonBridge
Returns PythonBridge
Set Signature
set py(
pythonBridge):void
Parameters
| Parameter | Type |
|---|---|
pythonBridge | PythonBridge |
Returns void
Defined in generated/model_selection/StratifiedKFold.ts:53
Methods
dispose()
dispose():
Promise<void>
Disposes of the underlying Python resources.
Once dispose() is called, the instance is no longer usable.
Returns Promise<void>
Defined in generated/model_selection/StratifiedKFold.ts:105
get_metadata_routing()
get_metadata_routing(
opts):Promise<any>
Get metadata routing of this object.
Please check User Guide on how the routing mechanism works.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.routing? | any | A MetadataRequest encapsulating routing information. |
Returns Promise<any>
Defined in generated/model_selection/StratifiedKFold.ts:124
get_n_splits()
get_n_splits(
opts):Promise<number>
Returns the number of splitting iterations in the cross-validator.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.groups? | any | Always ignored, exists for compatibility. |
opts.X? | any | Always ignored, exists for compatibility. |
opts.y? | any | Always ignored, exists for compatibility. |
Returns Promise<number>
Defined in generated/model_selection/StratifiedKFold.ts:158
init()
init(
py):Promise<void>
Initializes the underlying Python resources.
This instance is not usable until the Promise returned by init() resolves.
Parameters
| Parameter | Type |
|---|---|
py | PythonBridge |
Returns Promise<void>
Defined in generated/model_selection/StratifiedKFold.ts:66
split()
split(
opts):Promise<ArrayLike>
Generate indices to split data into training and test set.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.groups? | any | Always ignored, exists for compatibility. |
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.y? | ArrayLike | The target variable for supervised learning problems. Stratification is done based on the y labels. |
Returns Promise<ArrayLike>