0
$\begingroup$

I have two classes w1 and w2 and we are working with 2D space. The density of each of the two classes are the following:

\begin{equation} p(x = {(x_{1}, x_{2})}'| w_{1}) = \frac{1}{4}\cdot e ^{-\frac{x_{1}+ x_{2}}{2}} \end{equation} \begin{equation} p(x = {(x_{1}, x_{2})}'| w_{2}) = \frac{1}{16}\cdot x_{1}x_{2} \cdot e ^{-\frac{x_{1}+ x_{2}}{2}} \end{equation}

Classes have equal prior probabilities. Solving $p(x|w_1)=p(x|w_2)$ to find the decision boundary yields the curve $x_1x_2=4$.

How can we calculate the error of the bayesian classifier? Here is the equation for the error's expected value. enter image description here

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.