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README.md

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 # citation-analysis
 Project repo for Computational Linguistics Team Laboratory at the University of Stuttgart
+
+
+### **Evaluation**
+we plan to implement and use ***f1_score*** metric for evaluation of our classifier
+
+> F1 score is a weighted average of Precision and Recall(or Harmonic Mean between Precision and Recall).  
+> The formula for F1 Score is:
+> F1 = 2 * (precision * recall) / (precision + recall)
+
+```python
+eval.metrics.f1_score(y_true, y_pred, labels, average)
+```
+#### Parameters:
+**y_true** : 1-d array or list of gold class values  
+**y_pred** : 1-d array or list of estimated values returned by a classifier  
+**labels** : list of labels/classes  
+**average**: string - [None, 'micro', 'macro'] If None, the scores for each class are returned.