ml_grid.model_classes.xgb_classifier_class

XGBoost Classifier.

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

Classes

XGBClassifierClass

Initializes the XGBClassifierClass.

Module Contents

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

Initializes the XGBClassifierClass.

The XGB_class_class wraps the XGBoost classifier algorithm, allowing for easy configuration and use within a grid search or Bayesian optimization framework by setting up a customizable parameter space.

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: xgboost.XGBClassifier

method_name: str = 'XGBClassifier'

parameter_vector_space: ml_grid.util.param_space.ParamSpace

parameter_space: Dict[str, Any]