sklearn.utils
.indexable#
- sklearn.utils.indexable(*iterables)[source]#
Make arrays indexable for cross-validation.
Checks consistent length, passes through None, and ensures that everything can be indexed by converting sparse matrices to csr and converting non-interable objects to arrays.
- Parameters:
- *iterables{lists, dataframes, ndarrays, sparse matrices}
List of objects to ensure sliceability.
- Returns:
- resultlist of {ndarray, sparse matrix, dataframe} or None
Returns a list containing indexable arrays (i.e. NumPy array, sparse matrix, or dataframe) or
None
.
Examples
>>> from sklearn.utils import indexable >>> from scipy.sparse import csr_matrix >>> import numpy as np >>> iterables = [ ... [1, 2, 3], np.array([2, 3, 4]), None, csr_matrix([[5], [6], [7]]) ... ] >>> indexable(*iterables) [[1, 2, 3], array([2, 3, 4]), None, <3x1 sparse matrix ...>]