RMSE is a commonly used evaluation metric for regression tasks. It measures the average deviation between the predicted values and the actual values, taking the square root of the mean of the squared differences. In the context of this contest, the RMSE will be calculated to assess the accuracy of the interest rate predictions.

RMSE is defined as the square root of the mean squared error (MSE), which is the average squared difference between the predicted values of the model and the true values of the data.

The RMSE is calculated using the following formula:

$$\displaystyle RMSE = \sqrt{\frac{\Sigma_{i=1}^{i=n}(y_i-\hat{y_i})}{n}}$$

Where n is the number of observations in the data, y_i is the true value of the i-th observation, and ŷ_i is the predicted value of the i-th observation.