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"""
Quadratic Discriminant Analysis (QDA) Classifier setup.
Features:
- Uses `QuadraticDiscriminantAnalysis`.
- Works for binary and multi-class tasks.
- Default scoring: 'accuracy'.
Considerations:
- `reg_param` can be tuned to control regularization.
"""
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
estimator = QuadraticDiscriminantAnalysis()
param_grid = {
'model__reg_param': [0.0, 0.1, 0.5],
# Preprocessing params
#'preprocessor__num__imputer__strategy': ['mean','median'],
#'preprocessor__num__scaler__with_mean': [True,False],
#'preprocessor__num__scaler__with_std': [True,False],
}
default_scoring = 'accuracy'
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