The evaluation metric for this competition is
Log Loss
$$log loss = -\frac{1}{N}\sum_{i=1}^N {(y_i\log(p_i) + (1 - y_i)\log(1 - p_i))}$$
where N is the number of observations, \\(log\\) is the natural logarithm, \\(y_{i}\\) is the binary target, and \\(p_{i}\\) is the predicted probability that \\(y_i\\) equals 1.
Note: the actual submitted predicted probabilities are replaced with \\(max(min(p,1-10^{-15}),10^{-15})\\).
Submission File
For every observation in the test dataset
, submission files should contain two columns: ID and PredictedProb. The file should contain a header and have the following format:
ID,PredictedProb
0,0.5
1,0.5
2,0.5
7,0.5
etc.