Mean Squared Error
#Math
Topics
$\displaystyle \text{MSE}=\frac{1}{n}\sum_{i = 1}^{n}(y_{i}-\hat{y}_{i})^{2}$
- $\displaystyle y_{i}$ is the value of a data point from the test data
- $\displaystyle \hat{y}{i}$ is the value of our prediction at $\displaystyle x{i}$ according to the model built upon training data