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I basically follow the exact step with your tutorial on /tutorial/ptranking_demo_ltr.ipynb file. I used the same dataset from LETOR 4.0 MQ2008 but got a KeyError in this line of code lambdarank_losses, lambdarank_train_ndcgs, lambdarank_test_ndcgs = ltr_evaluator.naive_train(ranker=lambdarank, eval_dict=eval_dict, train_data=train_data, test_data=test_data). It was fine with the RankNet though.
Error:
label_type = kwargs['label_type']
32 assert LABEL_TYPE.MultiLabel == label_type
33 assert 'presort' in kwargs and kwargs['presort'] is True # aiming for direct usage of ideal ranking
KeyError: 'label_type'
The text was updated successfully, but these errors were encountered:
I basically follow the exact step with your tutorial on /tutorial/ptranking_demo_ltr.ipynb file. I used the same dataset from LETOR 4.0 MQ2008 but got a KeyError in this line of code
lambdarank_losses, lambdarank_train_ndcgs, lambdarank_test_ndcgs = ltr_evaluator.naive_train(ranker=lambdarank, eval_dict=eval_dict, train_data=train_data, test_data=test_data)
. It was fine with the RankNet though.Error:
The text was updated successfully, but these errors were encountered: