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"""
Contains routines for preprocessing data frames.
"""
from dataclasses import dataclass
from .preprocessor import _Preprocessor
from .validate import _validate
[docs]@dataclass(repr=False)
class Seasonal(_Preprocessor):
"""
The Seasonal preprocessor extracts seasonal data from time stamps.
The preprocessor automatically iterates through
all time stamps in any data frame and extracts
seasonal parameters.
These include:
- year
- month
- weekday
- hour
- minute
The algorithm also evaluates the potential
usefulness of any extracted seasonal parameter.
Parameters that are unlikely to be useful are
not included.
Example:
.. code-block:: python
seasonal = getml.preprocessors.Seasonal()
pipe = getml.Pipeline(
population=population_placeholder,
peripheral=[order_placeholder, trans_placeholder],
preprocessors=[seasonal],
feature_learners=[feature_learner_1, feature_learner_2],
feature_selectors=feature_selector,
predictors=predictor,
share_selected_features=0.5
)
"""
[docs] def validate(self, params=None):
"""Checks both the types and the values of all instance
variables and raises an exception if something is off.
Args:
params (dict, optional):
A dictionary containing
the parameters to validate. If not is passed,
the own parameters will be validated.
"""
_validate(self, params)