no_split

Empty Data Splitter class.

Module Contents

Classes Summary

NoSplit

Does not split the training data into training and validation sets.

Contents

class evalml.preprocessing.data_splitters.no_split.NoSplit(random_seed=0)[source]

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.

Parameters

random_seed (int) – The seed to use for random sampling. Defaults to 0. Not used.

Methods

get_n_splits

Return the number of splits of this object.

is_cv

Returns whether or not the data splitter is a cross-validation data splitter.

split

Divide the data into training and testing sets, where the testing set is empty.

static get_n_splits()[source]

Return the number of splits of this object.

Returns

Always returns 0.

Return type

int

property is_cv(self)

Returns whether or not the data splitter is a cross-validation data splitter.

Returns

If the splitter is a cross-validation data splitter

Return type

bool

split(self, X, y=None)[source]

Divide the data into training and testing sets, where the testing set is empty.

Parameters
  • X (pd.DataFrame) – Dataframe of points to split

  • y (pd.Series) – Series of points to split

Returns

Indices to split data into training and test set

Return type

list