The evaluation metric for this competition is  the
micro-averaged F1-Score
. The F1 score measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn).  The micro-averaged computation of the true positives is the sum of all true positives across all classes. Similarly for the micro-averaged computations of the false positives and the false negatives. The micro-averaged F1 score is given by:
\[ F1 = 2\frac{p \cdot r}{p+r}\ \ \mathrm{where}\ \ p = \frac{\sum_{k\in C} tp_k}{\sum_{k\in C} tp_k+\sum_{k\in C} fp_k},\ \ r = \frac{\sum_{k\in C} tp_k}{\sum_{k\in C} tp_k+\sum_{k\in C} fn_k}\]