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"""
Support Vector Classifier setup.
Features:
- Uses `SVC` from scikit-learn.
- Handles binary classification naturally, and multi-class via OvR by default.
- Default scoring: 'accuracy'.
Considerations:
- `C` and `kernel` are key parameters.
- If `kernel='rbf'`, also tune `gamma`.
"""
from sklearn.svm import SVC
estimator = SVC(random_state=42)
param_grid = {
'model__C': [0.1, 1.0], # Reduced the range
'model__kernel': ['linear'], # Focused on linear kernel
'model__gamma': ['scale'], # Fixed the gamma to one option
# Preprocessing params
#'preprocessor__num__imputer__strategy': ['mean'],
#'preprocessor__num__scaler__with_mean': [True],
#'preprocessor__num__scaler__with_std': [True],
}
default_scoring = 'accuracy'
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