"""
This module provides a Linear Discriminant Analysis (LDA) model wrapper, inheriting
from `aiqclib.common.base.scikit_learn_model_base.SklearnModelBase`.
It facilitates training, prediction, and evaluation of an LDA classifier using
Polars DataFrames, converting them to Pandas for compatibility with the
`sklearn` library.
"""
from typing import Dict, Any
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as SklearnLDA
from aiqclib.common.base.config_base import ConfigBase
from aiqclib.common.base.scikit_learn_model_base import SklearnModelBase
[docs]
class LinearDiscriminantAnalysis(SklearnModelBase):
"""
A Linear Discriminant Analysis (LDA) model wrapper class for training and testing.
Inherits from :class:`SklearnModelBase` to reuse common Scikit-Learn API logic.
Features include:
- Automatic application of ``model_params`` from the YAML config, if defined;
otherwise, uses default hyperparameters.
- Uses ``sklearn.discriminant_analysis.LinearDiscriminantAnalysis``.
.. note::
This class sets :attr:`expected_class_name` to ``"LinearDiscriminantAnalysis"``.
Note that LDA in scikit-learn does not support the ``n_jobs`` parameter.
"""
expected_class_name: str = "LinearDiscriminantAnalysis"
short_name: str = "LDA"
def __init__(self, config: ConfigBase) -> None:
"""
Initialize the LDA model with default or user-specified parameters.
:param config: A configuration object providing model parameters.
:type config: aiqclib.common.base.config_base.ConfigBase
"""
super().__init__(config=config)
self.model_params: Dict[str, Any] = {
"solver": "svd",
"shrinkage": None,
"priors": None,
"n_components": None,
"store_covariance": False,
"tol": 1.0e-4,
}
# Update model parameters with config step parameters
model_params = self.config.get_model_params(
self.expected_class_name, self.short_name
)
self.model_params.update(model_params)
self.allow_na = False
def _get_model_class(self) -> Any:
"""
Return the Scikit-Learn LinearDiscriminantAnalysis class.
:return: The LinearDiscriminantAnalysis class from scikit-learn.
:rtype: type
"""
return SklearnLDA