ruidan / Unsupervised-Aspect-Extraction

Code for acl2017 paper "An unsupervised neural attention model for aspect extraction"
Apache License 2.0
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Predict_label on test data #22

Open esskay0000 opened 5 years ago

esskay0000 commented 5 years ago

The code runs fine and results as per table 6 of the paper are produced too, though with slight variance. But is there a script to label (possibly using predict_label) the individual texts in test dataset? else, how is evaluation script getting to calculating F-scores?

ruidan commented 5 years ago

You may read the paper section 5.2 and the script evaluation.py to understand how the F-scores are computed on test set.

esskay0000 commented 5 years ago

Thanks for the response. But the question was to get the predict_label for each observation text in test file. To be clear, this predict_label is compared with true_label, to arrive at F-score and other confusion matrix. F-score generation and output is being replicated by me but do not get to see which textx are mis-classified to infer results. Please suggest how to get predicted labels for each text in test.txt