The evaluation metric for this competition is
[Root Mean Squared Logarithmic Error](https://www.kaggle.com/wiki/RootMeanSquaredLogarithmicError)
.
The RMSLE is calculated as
$$
\epsilon = \sqrt{\frac{1}{n} \sum_{i=1}^n (\log(p_i + 1) - \log(a_i+1))^2 }
$$
Where:
\\(\epsilon\\) is the RMSLE value (score)
\\(n\\) is the total number of observations in the (public/private) data set,
\\(p_i\\) is your prediction of demand, and
\\(a_i\\) is the actual demand for \\(i\\).
\\(\log(x)\\) is the natural logarithm of \\(x\\)
Submission File
For every row in the dataset
, submission files should contain two columns: id and Demanda_uni_equi.  The id corresponds to the column of that id in the test.csv. The file should contain a header and have the following format:
id,Demanda_uni_equil
0,1
1,0
2,500
3,100
etc.