[{'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:"""\nGridSearchCV\n\nGridSearchCV\nhttps://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html\nhttps://datascienceschool.net/view-notebook/ff4b5d491cc34f94aea04baca86fbef8/\n"""\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn import metrics\n\n#RidgeL2alpha\nridge = Ridge()\n\n#Ridge\nridge_params = {\'max_iter\':[3000],\'alpha\':[0.001,0.01,0.1,1,10,100,1000]}\nrmsle_scorer = metrics.make_scorer(rmsle,greater_is_better=False)\ngrid_ridge = GridSearchCV(ridge,ridge_params,scoring=rmsle_scorer,cv=5)\n\ngrid_ridge.fit(train,yLabelslog)\npreds = grid_ridge.predict(train)\nprint(grid_ridge.best_params_)\nprint(\'RMSLE Value for Ridge Regression {}\'.format(rmsle(np.exp(yLabelslog),np.exp(preds),False)))\''}, {'role': 'assistant', 'content': 'modelling'}]