no_variance_data_check¶
Data check that checks if the target or any of the features have no variance.
Module Contents¶
Classes Summary¶
Check if the target or any of the features have no variance. |
Contents¶
-
class
evalml.data_checks.no_variance_data_check.NoVarianceDataCheck(count_nan_as_value=False)[source]¶ Check if the target or any of the features have no variance.
- Parameters
count_nan_as_value (bool) – If True, missing values will be counted as their own unique value. Additionally, if true, will return a DataCheckWarning instead of an error if the feature has mostly missing data and only one unique value. Defaults to False.
Methods
Return a name describing the data check.
Check if the target or any of the features have no variance (1 unique value).
-
name(cls)¶ Return a name describing the data check.
-
validate(self, X, y)[source]¶ Check if the target or any of the features have no variance (1 unique value).
- Parameters
X (pd.DataFrame, np.ndarray) – The input features.
y (pd.Series, np.ndarray) – The target data.
- Returns
dict of warnings/errors corresponding to features or target with no variance.
- Return type
dict