(i) Show that any binary classifier g : {0, 1}D {0, 1} can be implemented as a decision tree classifier. That is, for any classifier g there exists a decision tree classifier T with k nodes n, , , , , nk (each ni with a corresponding threshhold ti), such that g(x)-T(a for all x E {0, 1) D aximum height of such a tree T (from part (i))? For what function g is the bound tight? (i) Show that any binary classifier g : {0, 1}D {0, 1} can be implemented as a decision tree classifier. That is, for any classifier g there exists a decision tree classifier T with k nodes n, , , , , nk (each ni with a corresponding threshhold ti), such that g(x)-T(a for all x E {0, 1) D aximum height of such a tree T (from part (i))? For what function g is the bound tight