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"""
Contains routines for preprocessing data frames.
"""
from dataclasses import dataclass, field
from typing import ClassVar, List
from getml.feature_learning.aggregations import mapping as mapping_aggregations
from getml.feature_learning.aggregations import _Aggregations
from .validate import _validate
from .preprocessor import _Preprocessor
[docs]@dataclass(repr=False)
class Mapping(_Preprocessor):
"""
A mapping preprocessor maps categorical values, discrete values and individual
words in a text field to numerical values. These numerical values are retrieved
by aggregating targets in the relational neighbourhood.
You are particularly encouraged to use the mapping preprocessor in combination with
:class:`~getml.feature_learning.FastProp`.
Refer to the :ref:`User guide <mappings>` for more information.
Args:
aggregation (List[:class:`~getml.feature_learning.aggregations`], optional):
The aggregation function to use over the targets.
Must be from :mod:`~getml.feature_learning.aggregations`.
min_freq (int, optional):
The minimum number of targets required for a value to be included in
the mapping. Range: [0, :math:`\\infty`]
multithreading (bool, optional):
Whether you want to apply multithreading.
Example:
.. code-block:: python
mapping = getml.preprocessors.Mapping()
pipe = getml.Pipeline(
population=population_placeholder,
peripheral=[order_placeholder, trans_placeholder],
preprocessors=[mapping],
feature_learners=[feature_learner_1, feature_learner_2],
feature_selectors=feature_selector,
predictors=predictor,
share_selected_features=0.5
)
"""
agg_sets: ClassVar[_Aggregations] = mapping_aggregations
aggregation: List[str] = field(default_factory=lambda: mapping_aggregations.Default)
min_freq: int = 30
multithreading: bool = True
[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.
"""
params = _validate(self, params)
if not all([agg in mapping_aggregations.All for agg in params["aggregation"]]):
raise ValueError(
"'aggregation' must be from Mapping.agg_sets.All, "
+ "meaning from the following set: "
+ str(mapping_aggregations.All)
+ "."
)
if not isinstance(params["min_freq"], int):
raise TypeError("'min_freq' must be an int.")
if params["min_freq"] < 0:
raise TypeError("'min_freq' cannot be negative.")
if not isinstance(params["multithreading"], bool):
raise TypeError("'multithreading' must be a bool.")