SVC syntax
时间: 2023-10-18 12:32:05 浏览: 40
The syntax for using SVC (Support Vector Classifier) in scikit-learn is as follows:
```python
from sklearn.svm import SVC
# Create an instance of SVC
model = SVC(C=1.0, kernel='rbf', gamma='scale')
# Train the model
model.fit(X_train, y_train)
# Make predictions
y_pred = model.predict(X_test)
```
Here, `C` is the regularization parameter that controls the trade-off between achieving a low training error and a low testing error. It is usually set using cross-validation. `kernel` specifies the type of kernel function to be used ('linear', 'poly', 'rbf', 'sigmoid', etc.), and `gamma` is a parameter for certain kernel functions.
You can replace `X_train` and `y_train` with your training data, and `X_test` with your test data. After training, you can use `predict()` to make predictions on new data.