[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:#GradientBoosting (7)\nfrom sklearn.ensemble import GradientBoostingClassifier\n\nGBC_clf = GradientBoostingClassifier(n_estimators=2000, learning_rate=0.008, max_depth=1, random_state=1).fit(train_normalized, train_labels)\n\ntrainpred=GBC_clf.predict(train_normalized)\n#testpred=GBC_clf.predict(test_normalized)\n\n#print(metrics.accuracy_score(train_labels, trainpred))\n\n# GBC_acc=cross_val_score(GBC_clf,train_normalized,train_labels,cv=20,scoring='accuracy')\n\n# print(GBC_acc)\n# print(np.mean(GBC_acc))"}, {'role': 'assistant', 'content': "['modelling']"}]