# Introduction

Loss function (or cost function) is widely used for measuring the differences between predicted goal and real value. In different scenario, user should choose different loss function. This blog will introduce some markable loss function and their usage conditions and disadvantages.

# Mean Square Error

\lambda(x) = C (t-x)^2

# Huber Loss / Smooth Mean Absolute Error

Huber Loss和Focal Loss的原理与实现

# MSE

Mean Squared Error (MSE), also known as mean squared deviation (MSD) in statics.

Mean Square Error – Wikipedia

# MAE

Mean Absolute Error (MAE)

Mean Absolute Error – Wikipedia

# Focal Loss

## References

Huber Loss和Focal Loss的原理与实现