mars.learn.utils.validation.
check_is_fitted
Perform is_fitted validation for estimator.
Checks if the estimator is fitted by verifying the presence of fitted attributes (ending with a trailing underscore) and otherwise raises a NotFittedError with the given message.
This utility is meant to be used internally by estimators themselves, typically in their own predict / transform methods.
estimator (estimator instance) – estimator instance for which the check is performed.
attributes (str, list or tuple of str, default=None) –
Attribute name(s) given as string or a list/tuple of strings Eg.: ["coef_", "estimator_", ...], "coef_"
["coef_", "estimator_", ...], "coef_"
If None, estimator is considered fitted if there exist an attribute that ends with a underscore and does not start with double underscore.
msg (str, default=None) –
The default error message is, “This %(name)s instance is not fitted yet. Call ‘fit’ with appropriate arguments before using this estimator.”
For custom messages if “%(name)s” is present in the message string, it is substituted for the estimator name.
Eg. : “Estimator, %(name)s, must be fitted before sparsifying”.
all_or_any (callable, {all, any}, default=all) – Specify whether all or any of the given attributes must exist.
None
NotFittedError – If the attributes are not found.