`mapie.subsample`.Subsample¶

class mapie.subsample.Subsample(n_resamplings: int = 30, n_samples: Optional[int] = None, replace: bool = True, random_state: Optional[Union[int, numpy.random.mtrand.RandomState]] = None)[source]¶

Generate a sampling method, that resamples the training set with possible bootstraps. It can replace KFold or LeaveOneOut as cv argument in the MAPIE class.

Parameters

n_resamplingsint: Number of resamplings. By default 30.
n_samples: int: Number of samples in each resampling. By default None, the size of the training set.
replace: bool: Whether to replace samples in resamplings or not. By default True.
random_state: Optional[Union[int, RandomState]]: int or RandomState instance. By default None

Examples

>>> import numpy as np
>>> from mapie.subsample import Subsample
>>> cv = Subsample(n_resamplings=2,random_state=0)
>>> X = np.array([1,2,3,4,5,6,7,8,9,10])
>>> for train_index, test_index in cv.split(X):
...    print(f"train index is {train_index}, test index is {test_index}")
train index is [5 0 3 3 7 9 3 5 2 4], test index is [1 6 8]
train index is [7 6 8 8 1 6 7 7 8 1], test index is [0 2 3 4 5 9]

__init__(n_resamplings: int = 30, n_samples: Optional[int] = None, replace: bool = True, random_state: Optional[Union[int, numpy.random.mtrand.RandomState]] = None) → None[source]¶

get_n_splits(*args: Any, **kargs: Any) → int[source]¶

Returns the number of splitting iterations in the cross-validator.

Returns

int: Returns the number of splitting iterations in the cross-validator.

split(X: numpy.ndarray[Any, numpy.dtype[numpy._typing._array_like._ScalarType_co]], *args: Any, **kargs: Any) → Generator[Tuple[numpy.ndarray[Any, numpy.dtype[numpy._typing._array_like._ScalarType_co]], numpy.ndarray[Any, numpy.dtype[numpy._typing._array_like._ScalarType_co]]], None, None][source]¶

Generate indices to split data into training and test sets.

Parameters

XNDArray of shape (n_samples, n_features): Training data.

Yields

trainNDArray of shape (n_indices_training,): The training set indices for that split.
testNDArray of shape (n_indices_test,): The testing set indices for that split.