text: from sklearn.linear_model import RidgeClassifier
  from sklearn.model_selection import GridSearchCV
  
  def ridge_classification(X_train, y_train, X_test):
    print("[Executing]: Running Ridge Regression model ...\n")
  
    # Model Fitting
    model = RidgeClassifier(random_state=49)
  
    parameters = {'alpha':[1, 10]}
    final_model = GridSearchCV(model, parameters, scoring='neg_mean_squared_error', cv=5)
    final_model.fit(X_train, y_train)
  
    # Predictions on test dataset
    y_pred = final_model.predict(X_test)
    
    return y_pred