Loss Function

Definition

Let $\theta \in \Omega$ be a parameter, $X:=u(X_1,X_2,\dots ,X_n)$ be a Statistic for the parameter $\theta$, and $\delta (x)$ be a Decision Function

A loss function is a non-negative function defined as $L(\theta ,\delta (x))$

It indicates the difference or discrepancy between $\theta$ and $\delta (x)$

Examples

• Absolute Error Loss
• Squared Error Loss
• Sum of Squared Errors Loss
• Cross-Entropy Loss
• Goal Post Error Loss
• Huber Loss
• Binary Loss
• Triplet Loss
• Pairwise Loss