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$1,...,$ nk $($each ni with a corresponding

threshold ti$),$ such that g$($x$)=$ T$($x$)$ for all x in $\{0,1\}$

D$.$