[{'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:def get_batches_for_mlp(ser, batch_size, horizon, n_lags, mimic_lstm=False):\n"""\nConverts time series to batches\nrepresented as data matrices.\n@type ser: pandas.Series\n@type batch_size: int\n@type horizon: int\n@type n_lags: int\n@type mimic_lstm: bool\n@rtype: list(tuple(numpy.ndarray))\n"""\ndf = take_ahead_and_lagged_values(ser, horizon, n_lags)\nif mimic_lstm:\npass\nn_batches = (len(ser) - horizon - n_lags) // batch_size\ndf = df.iloc[-(n_batches*batch_size + horizon):-horizon, :]\nx_array = df.iloc[:, :-horizon].values.reshape((n_batches, -1, n_lags + 1))\ny_array = df.iloc[:, -horizon:].values.reshape((n_batches, -1, horizon))\nreturn list(zip(x_array, y_array))'}, {'role': 'assistant', 'content': 'modelling'}]