ml_grid.model_classes.logistic_regression_class

Logistic Regression Classifier.

This module contains the LogisticRegression_class, which is a configuration class for the LogisticRegression. It provides parameter spaces for grid search and Bayesian optimization.

Classes

LogisticRegressionClass

Initializes the LogisticRegressionClass.

Module Contents

class ml_grid.model_classes.logistic_regression_class.LogisticRegressionClass(X: pandas.DataFrame | None = None, y: pandas.Series | None = None, parameter_space_size: str | None = None)

Initializes the LogisticRegressionClass.

Parameters:

• X (Optional[pd.DataFrame]) – Feature matrix for training. Defaults to None.

• y (Optional[pd.Series]) – Target vector for training. Defaults to None.

• parameter_space_size (Optional[str]) – Size of the parameter space for optimization. Defaults to None.

Raises:

ValueError – If parameter_space_size is not a valid key (though current implementation does not explicitly raise this).

X: pandas.DataFrame | None = None

y: pandas.Series | None = None

algorithm_implementation: sklearn.linear_model.LogisticRegression

method_name: str = 'LogisticRegression'

parameter_vector_space: ml_grid.util.param_space.ParamSpace

parameter_space: List[Dict[str, Any]]