[{'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 find_host(probabilities: numpy.ndarray, atlas_id: int) -> int:\n"""Finds the host galaxy associated with an ATLAS object.\nArguments\n---------\nprobabilities\n(N,) array of predicted probabilities of SWIRE objects.\natlas_id\nID of the ATLAS object to find the host of.\nReturns\n-------\nint\nID of predicted host galaxy.\n"""\nwith h5py.File(CROWDASTRO_PATH, \'r\') as cr, h5py.File(TRAINING_PATH, \'r\') as tr:\nir_distances = cr[\'/atlas/cdfs/numeric\'][atlas_id, ATLAS_DIST_IDX:]\nassert ir_distances.shape[0] == tr[\'features\'].shape[0]\nnearby = sorted((ir_distances <= NEARBY).nonzero()[0])\nnearby_probabilities = probabilities[nearby]\nbest_index = nearby_probabilities.argmax()\nbest_index = nearby[best_index]  # Convert back into an IR index.\nreturn best_index'}, {'role': 'assistant', 'content': 'data_exploration'}]