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"""
Random Forest Classifier setup.
Features:
- Uses `RandomForestClassifier` from scikit-learn.
- Good general-purpose model for binary and multi-class tasks.
- Default scoring: 'accuracy'.
"""
from sklearn.ensemble import RandomForestClassifier
estimator = RandomForestClassifier(random_state=42)
param_grid = {
'model__n_estimators': [100],
'model__max_depth': [None, 10],
'model__min_samples_split': [2, 5],
'model__min_samples_leaf': [1],
# 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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