sklearn.exceptions.ConvergenceWarning

class sklearn.exceptions.ConvergenceWarning[source]

Custom warning to capture convergence problems

Attributes
args

Examples

>>> import numpy as np
>>> import warnings
>>> from sklearn.cluster import KMeans
>>> from sklearn.exceptions import ConvergenceWarning
>>> warnings.simplefilter("always", ConvergenceWarning)
>>> X = np.asarray([[0, 0],
...                 [0, 1],
...                 [1, 0],
...                 [1, 0]])  # last point is duplicated
>>> with warnings.catch_warnings(record=True) as w:
...     km = KMeans(n_clusters=4).fit(X)
...     print(w[-1].message)
Number of distinct clusters (3) found smaller than n_clusters (4).
Possibly due to duplicate points in X.

Changed in version 0.18: Moved from sklearn.utils.

Methods

with_traceback()

Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
with_traceback()

Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.