Seqeval

Update setup.py to relax version pinning, fix 65

In strict mode, speed up the evaluation.
About 13 times faster.

Fixes 62

Enable to compute macro/weighted/perClass f1, recall, and precision 61

F1 score

python
>>> from seqeval.metrics import f1_score
>>> y_true = [['O', 'O', 'B-MISC', 'I-MISC', 'B-MISC', 'O', 'O'], ['B-PER', 'I-PER', 'O']]
>>> y_pred = [['O', 'O', 'B-MISC', 'I-MISC', 'B-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
>>> f1_score(y_true, y_pred, average=None)
array([0.5, 1. ])
>>> f1_score(y_true, y_pred, average='micro')

Add length check to classification_report v1 59

Add BILOU as a scheme 56

In some cases, the behavior of the current classification_report is not enough. In the new classification_report, we can specify the evaluation scheme explicitly. This resolved the following issues:

Fix 23
Fix 25
Fix 35
Fix 36
Fix 39