I've been working on a programming project on classification with 3 classes, and I'm interested in comparing my results to what I'd expect from pure noise. So I have the following question:
Let $X,Y,Z$ be uniformly distributed over $\{(x,y,z)\in [0,1]^3:x+y+z=1\}$. What is $E \max (X,Y,Z)$?
Thanks
Sorry for editing after the fact. I'm also interested in $E(-X \log ( X )-Y\log ( Y )-Z \log (Z))$
I'm interpreting "$X$, $Y$, $Z$ uniformly distributed over $S:=\bigl\{(x,y,z)\in[0,1]^3\bigm| x+y+z=1\bigr\}$" as uniformly distributed with respect to surface measure on the equilateral triangle $S$. This measure is proportional to the euclidean measure of the projection $S'$ of $S$ to the $(x,y)$-plane.
The three medians $x=y$, $y=z$, $z=x$ partition $S$ into six congruent parts corresponding to the order $\leq$ of $x$, $y$, $z$. It is sufficient to compute the expected value $E$ in the part $T\subset S$ corresponding to $y\leq x\leq z=1-x-y$. This part $T$ projects to the triangle $$T'=\bigl\{(x,y)\bigm| 0\leq y\leq x, \ x\leq 1-x-y\bigr\}\subset S'\ .$$ The vertices of $T'$ are $(0,0)$, $({1\over2},0)$, $({1\over3},{1\over3})$. On $T$ we have $$\max\{x,y,z\}=z=1-x-y\ .$$ We therefore obtain $$E={\int_{T'}(1-x-y)\>{\rm d}(x,y)\over{\rm area}(T')}=\ldots={11\over18}\ .$$