# Bayes Classification Problem

Let we have 2 classes with their densties : p(x| w1)=$$\tfrac12e^{-|x|}$$

P(x|w2) = $$e^{-2|x-2|}$$

Where x is a one dimension feature vector . Now it is required to be known where to place the decsision boundry so that the probabilites of errors from both classes are equal to each other. What I have done is that I have equated both probability densty functions and then I have solved this equation to get two solutions one x= 1.10 and x=4.69. Which means that we kan place the boundry at x= 1.10 or x = 4.69. So am I right ? Or did I do something wrong ? Also , can you help me please to sketch both density functions to visualize them ?