Enhancement/strict mode

[Hironsan]

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

For backward compatibility, we need to specify mode='strict' to use the new classification_report:

>>> from seqeval.metrics import classification_report
>>> y_true = [['B-A', 'B-B', 'O', 'B-A']]
>>> y_pred = [['O', 'B-B', 'B-C', 'B-A']]
>>> print(classification_report(y_true, y_pred, mode='strict'))
/Users/hironsan/Workspace/seqeval/venv/lib/python3.8/site-packages/seqeval-0.0.20.dev11+g52f742b.d20201011-py3.8.egg/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
              precision    recall  f1-score   support

           A       1.00      0.50      0.67         2
           B       1.00      1.00      1.00         1
           C       0.00      0.00      0.00         0

   micro avg       0.67      0.67      0.67         3
   macro avg       0.67      0.50      0.56         3
weighted avg       1.00      0.67      0.78         3