| LETTOR | MQ2007_Super % MQ2008_Super % MQ2007_Semi % MQ2008_Semi |
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| MSLRWEB | MSLRWEB10K % MSLRWEB30K |
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| Yahoo_LTR | Set1 % Set2 |
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| ISTELLA_LTR | Istella_S | Istella | Istella_X |
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"""
debug = True # in a debug mode, we just check whether the model can operate
config_with_json = True # specify configuration with json files or not
evaluator = TreeLTREvaluator()
if config_with_json: # specify configuration with json files
# the directory of json files
dir_json = '/Users/dryuhaitao/WorkBench/Dropbox/CodeBench/GitPool/wildltr_ptranking/testing/ltr_tree/json/'
evaluator.run(debug=debug,
model_id='LightGBMLambdaMART',
config_with_json=config_with_json,
dir_json=dir_json)
else:
#data_id = 'MQ2008_Super'
data_id = 'MSLRWEB30K'
#dir_data = '/home/dl-box/WorkBench/Datasets/L2R/LETOR4.0/MQ2008/'
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| Yahoo_LTR | Set1 % Set2 |
-----------------------------------------------------------------------------------------
| ISTELLA_LTR | Istella_S | Istella | Istella_X |
-----------------------------------------------------------------------------------------
"""
args_obj = ArgsUtil(given_root='./')
l2r_args = args_obj.get_l2r_args()
if l2r_args.model in LTR_ADHOC_MODEL:
evaluator = LTREvaluator(cuda=l2r_args.cuda)
elif l2r_args.model in LTR_ADVERSARIAL_MODEL:
evaluator = AdLTREvaluator(cuda=l2r_args.cuda)
elif l2r_args.model in LTR_TREE_MODEL:
evaluator = TreeLTREvaluator()
else:
args_obj.args_parser.print_help()
sys.exit()
print('Started evaluation with pt_ranking !')
evaluator.run(model_id=l2r_args.model,
dir_json=l2r_args.dir_json,
debug=l2r_args.debug,
config_with_json=True)
print('Finished evaluation with pt_ranking !')