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)

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.