GroupShuffleSplit
Shuffle-Group(s)-Out cross-validation iterator
Provides randomized train/test indices to split data according to a third-party provided group. This group information can be used to encode arbitrary domain specific stratifications of the samples as integers.
For instance the groups could be the year of collection of the samples and thus allow for cross-validation against time-based splits.
The difference between LeavePGroupsOut and GroupShuffleSplit is that the former generates splits using all subsets of size p unique groups, whereas GroupShuffleSplit generates a user-determined number of random test splits, each with a user-determined fraction of unique groups.
For example, a less computationally intensive alternative to LeavePGroupsOut(p=10) would be GroupShuffleSplit(test\_size=10, n\_splits=100).
Note: The parameters test\_size and train\_size refer to groups, and not to samples, as in ShuffleSplit.
Read more in the User Guide.
Python Reference (opens in a new tab)
Constructors
constructor()
Signature
new GroupShuffleSplit(opts?: object): GroupShuffleSplit;Parameters
| Name | Type | Description |
|---|---|---|
opts? | object | - |
opts.n_splits? | number | Number of re-shuffling & splitting iterations. Default Value 5 |
opts.random_state? | number | Controls the randomness of the training and testing indices produced. Pass an int for reproducible output across multiple function calls. See Glossary. |
opts.test_size? | number | If float, should be between 0.0 and 1.0 and represent the proportion of groups to include in the test split (rounded up). If int, represents the absolute number of test groups. If undefined, the value is set to the complement of the train size. The default will change in version 0.21. It will remain 0.2 only if train\_size is unspecified, otherwise it will complement the specified train\_size. Default Value 0.2 |
opts.train_size? | number | If float, should be between 0.0 and 1.0 and represent the proportion of the groups to include in the train split. If int, represents the absolute number of train groups. If undefined, the value is automatically set to the complement of the test size. |
Returns
Defined in: generated/model_selection/GroupShuffleSplit.ts:33 (opens in a new tab)
Properties
_isDisposed
boolean=false
Defined in: generated/model_selection/GroupShuffleSplit.ts:31 (opens in a new tab)
_isInitialized
boolean=false
Defined in: generated/model_selection/GroupShuffleSplit.ts:30 (opens in a new tab)
_py
PythonBridge
Defined in: generated/model_selection/GroupShuffleSplit.ts:29 (opens in a new tab)
id
string
Defined in: generated/model_selection/GroupShuffleSplit.ts:26 (opens in a new tab)
opts
any
Defined in: generated/model_selection/GroupShuffleSplit.ts:27 (opens in a new tab)
Accessors
py
Signature
py(): PythonBridge;Returns
PythonBridge
Defined in: generated/model_selection/GroupShuffleSplit.ts:62 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;Parameters
| Name | Type |
|---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/model_selection/GroupShuffleSplit.ts:66 (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/GroupShuffleSplit.ts:119 (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/GroupShuffleSplit.ts:136 (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/GroupShuffleSplit.ts:75 (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/GroupShuffleSplit.ts:183 (opens in a new tab)