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Hi,
I was wondering how you are actually calculating your scores.
y_true = np.array([hp.tag2idx[line.split()[1]] for line in open(f, 'r').read().splitlines() if len(line) > 0])
y_pred = np.array([hp.tag2idx[line.split()[2]] for line in open(f, 'r').read().splitlines() if len(line) > 0])
Hi,
I was wondering how you are actually calculating your scores.
y_true = np.array([hp.tag2idx[line.split()[1]] for line in open(f, 'r').read().splitlines() if len(line) > 0])
y_pred = np.array([hp.tag2idx[line.split()[2]] for line in open(f, 'r').read().splitlines() if len(line) > 0])
Can you explain what the above code means?
How does this translate to say recall = TP / TP + FN? Don't you have to use some multi-class method?
Also, why are you only taking the index where y_true>1? Is it because you do not want the Other tag to skew your results? Thanks!
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