Напомним, точность Multiclass модель

Question

Я хочу вычислить точность отзыва в контексте мультикласса:

def GetDocument(link):
    dataframe = pd.read_csv(link, encoding = "ISO-8859-1", sep = ',')
    return dataframe
Y_test = GetDocument('lstm_res.csv')
y_score = GetDocument('cnn_res.csv')

from sklearn.metrics import precision_recall_curve
from sklearn.metrics import average_precision_score

# For each class
precision = dict()
recall = dict()
average_precision = dict()
for i in range(n_classes):
    precision[i], recall[i], _ = precision_recall_curve(Y_test[:, i],
                                                        y_score[:, i])
    average_precision[i] = average_precision_score(Y_test[:, i], y_score[:, i])

# A "micro-average": quantifying score on all classes jointly
precision["micro"], recall["micro"], _ = precision_recall_curve(Y_test.ravel(),
    y_score.ravel())
average_precision["micro"] = average_precision_score(Y_test, y_score,
                                                     average="micro")
print('Average precision score, micro-averaged over all classes: {0:0.2f}'
      .format(average_precision["micro"]))

Однако я получаю следующую ошибку:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-319cf7b60667> in <module>()
      7 average_precision = dict()
      8 for i in range(110):
----> 9     precision[i], recall[i], _ = precision_recall_curve(Y_test[:, i],
     10                                                         y_score[:, i])
     11     average_precision[i] = average_precision_score(Y_test[:, i], y_score[:, i])

/export/home/opt/jupyterhub/conda/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2137             return self._getitem_multilevel(key)
   2138         else:
-> 2139             return self._getitem_column(key)
   2140 
   2141     def _getitem_column(self, key):

/export/home/opt/jupyterhub/conda/lib/python3.6/site-packages/pandas/core/frame.py in _getitem_column(self, key)
   2144         # get column
   2145         if self.columns.is_unique:
-> 2146             return self._get_item_cache(key)
   2147 
   2148         # duplicate columns & possible reduce dimensionality

/export/home/opt/jupyterhub/conda/lib/python3.6/site-packages/pandas/core/generic.py in _get_item_cache(self, item)
   1838         """Return the cached item, item represents a label indexer."""
   1839         cache = self._item_cache
-> 1840         res = cache.get(item)
   1841         if res is None:
   1842             values = self._data.get(item)

TypeError: unhashable type: 'slice'

Несколько советов? Спасибо