[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:from sklearn.linear_model import Ridge\n#Assiging different sets of alpha values to explore which can be the best fit for the model. \ntemp_msle = {}\nfor i in np.linspace(0, 40, 20):\n    ridge = Ridge(alpha= i, normalize=True)\n    #fit the model. \n    ridge.fit(X_train, y_train)\n    ## Predicting the target value based on "Test_x"\n    pred = ridge.predict(X_test)\n\n    msle = np.sqrt(metrics.mean_squared_log_error(np.exp(y_test), np.exp(pred)))\n    temp_msle[i] = msle'}, {'role': 'assistant', 'content': 'modelling'}]