[{'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:X = x_registered.values\nY = y_registered.values\nn_features = X.shape[1]\ntime_steps_reg = 18\nscaler_reg = StandardScaler()\nX = scaler_reg.fit_transform(X)\nX, Y = reshape_data(X, Y, time_steps_reg)\ndef model_reg():\nmodel = Sequential()\nmodel.add(GRU(100, input_shape=(time_steps_reg, n_features), return_sequences=True, activation=\'relu\'))\nmodel.add(GRU(100, input_shape=(time_steps_reg, n_features), activation=\'relu\'))\nmodel.add(Dense(100, activation=\'relu\'))\nmodel.add(Dense(100, activation=\'relu\'))\nmodel.add(Dense(100, activation=\'relu\'))\nmodel.add(Dense(100, activation=\'relu\'))\nmodel.add(Dense(1))\nmodel.add(Activation(\'linear\'))\nmodel.compile(loss=\'mean_squared_error\', optimizer=\'RMSprop\')\nreturn model\nkr_registered = KerasRegressor(build_fn=model_reg, nb_epoch=100, batch_size=5, verbose=2)\n%time kr_registered.fit(X, Y, callbacks=[TensorBoard( \\\nlog_dir=\'logs/reg_gru2dense4_ts\'+str(time_steps_reg)+\'_\'+datetime.now().strftime("%Y%m%d-%H%M"))])'}, {'role': 'assistant', 'content': "['modelling']"}]