I am studying the AdaBoost algorithm. The update rule for a weak hypothesis is:
$Dt+1(i) = Dt(i)exp(−αtyiht(xi))/zt $
where $zt$ is a normalization factor chosen so that $Dt+1$ is a distribution.
What does the 'normalization factor' mean? Could I have an explanation with an example, please?