"""Empty Data Splitter class."""
import numpy as np
from sklearn.model_selection._split import BaseCrossValidator
[docs]class NoSplit(BaseCrossValidator):
"""Does not split the training data into training and validation sets.
All data is passed as the training set, test data is simply an array of
`None`. To be used for future unsupervised learning, should not be used
in any of the currently supported pipelines.
Args:
random_seed (int): The seed to use for random sampling. Defaults to 0. Not used.
"""
def __init__(
self,
random_seed=0,
):
self.random_seed = random_seed
[docs] @staticmethod
def get_n_splits():
"""Return the number of splits of this object.
Returns:
int: Always returns 0.
"""
return 0
[docs] def split(self, X, y=None):
"""Divide the data into training and testing sets, where the testing set is empty.
Args:
X (pd.DataFrame): Dataframe of points to split
y (pd.Series): Series of points to split
Returns:
list: Indices to split data into training and test set
"""
return iter([(np.arange(X.shape[0]), [])])