K-Fold Cross Validation

#Computers
A way to validate the effectiveness of a machine learning model

$\displaystyle CV(\text{Model})=\frac{1}{K}\sum_{i = 1}^{K}L(\hat{f}{C{-i}}(C_{i}))$

• Lower value means better model
• $\displaystyle K$ is the number of chunks the data set is split into
• $\displaystyle \hat{f}{C{-i}}$ is the model fitted to the training set of all chunks that aren't $\displaystyle C_{i}$, the validation set
• $\displaystyle L$ is the loss function