Evaluation Metric
The evaluation metric for this competition is **Mean F Score**
. The F score, commonly used in information retrieval, 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 F1 score is given by:
\[ F1 = 2\frac{p \cdot r}{p+r}\ \ \mathrm{where}\ \ p = \frac{tp}{tp+fp},\ \ r = \frac{tp}{tp+fn} \]
The mean F1 evaluation metric used in this competition is to compute F1 score for each node first, then take the average
Submission Format
For every author in the dataset
, submission files should contain two columns: Id and Predicted. Predicted should be seperated by a space.
The file should contain a header and have the following format:
Id,Predicted
0,1 10 13
1,
2,9 10
3,10
etc.