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"""
Gaussian Naive Bayes Classifier setup.
Features:
- Uses `GaussianNB`.
- Suitable for binary and multi-class.
- Default scoring: 'accuracy'.
Considerations:
- `var_smoothing` is often the only parameter to tune.
"""
from sklearn.naive_bayes import GaussianNB
estimator = GaussianNB()
param_grid = {
'model__var_smoothing': [1e-1, 1e-3, 1e-5, 1e-7, 1e-9],
# 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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