KFold
K-Folds cross-validator
Provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).
Each fold is then used once as a validation while the k - 1 remaining folds form the training set.
Read more in the User Guide.
Python Reference (opens in a new tab)
Constructors
constructor()
Signature
new KFold(opts?: object): KFold;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. Otherwise, this parameter has no effect. Pass an int for reproducible output across multiple function calls. See Glossary. |
opts.shuffle? | boolean | Whether to shuffle the data before splitting into batches. Note that the samples within each split will not be shuffled. Default Value false |
Returns
Defined in: generated/model_selection/KFold.ts:27 (opens in a new tab)
Properties
_isDisposed
boolean=false
Defined in: generated/model_selection/KFold.ts:25 (opens in a new tab)
_isInitialized
boolean=false
Defined in: generated/model_selection/KFold.ts:24 (opens in a new tab)
_py
PythonBridge
Defined in: generated/model_selection/KFold.ts:23 (opens in a new tab)
id
string
Defined in: generated/model_selection/KFold.ts:20 (opens in a new tab)
opts
any
Defined in: generated/model_selection/KFold.ts:21 (opens in a new tab)
Accessors
py
Signature
py(): PythonBridge;Returns
PythonBridge
Defined in: generated/model_selection/KFold.ts:51 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;Parameters
| Name | Type |
|---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/model_selection/KFold.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/KFold.ts:105 (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/KFold.ts:122 (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/KFold.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. |
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/KFold.ts:165 (opens in a new tab)