exceptions

MissingValuesExogWarning (UserWarning)

Warning used to notify there are missing values in the exogenous data.

This warning occurs when the input data passed to the exog arguments contains missing values. Most machine learning models do not accept missing values, therefore the forecaster fit and predict may fail.

Source code in skforecast/exceptions/exceptions.py

class MissingValuesExogWarning(UserWarning):
    """
    Warning used to notify there are missing values in the exogenous data.
    This warning occurs when the input data passed to the `exog` arguments contains
    missing values. Most machine learning models do not accept missing values, therefore
    the forecaster `fit` and `predict` may fail.
    """
    def __init__(self, message):
        self.message = message

    def __str__(self):
        extra_message = (
            "\n You can suppress this warning using: "
            "warnings.simplefilter('ignore', category=MissingValuesExogWarning)"
        )
        return self.message + " " + extra_message

DataTypeWarning (UserWarning)

Warning used to notify there are dtypes in the exogenous data that are not

'int', 'float', 'bool' or 'category'. Most machine learning models do not accept other data types, therefore the forecaster fit and predict may fail.

Source code in skforecast/exceptions/exceptions.py

class DataTypeWarning(UserWarning):
    """
    Warning used to notify there are dtypes in the exogenous data that are not
    'int', 'float', 'bool' or 'category'. Most machine learning models do not
    accept other data types, therefore the forecaster `fit` and `predict` may fail.
    """
    def __init__(self, message):
        self.message = message

    def __str__(self):
        extra_message = (
            "\n You can suppress this warning using: "
            "warnings.simplefilter('ignore', category=ValueTypesExogWarning)"
        )
        return self.message + " " + extra_message

LongTrainingWarning (UserWarning)

Warning used to notify that a large number of models will be trained and the

the process may take a while to run.

Source code in skforecast/exceptions/exceptions.py

class LongTrainingWarning(UserWarning):
    """
    Warning used to notify that a large number of models will be trained and the
    the process may take a while to run.
    """
    def __init__(self, message):
        self.message = message

    def __str__(self):
        extra_message = (
            "\n You can suppress this warning using: "
            "warnings.simplefilter('ignore', category=LongTrainingWarning)"
        )
        return self.message + " " + extra_message