updating adaboost

doc/src/DecisionTrees/DecisionTrees.do.txt

@@ -1501,6 +1501,14 @@ where the function $I()$ is one if we misclassify and zero if we classify correc
 ===== Basic Steps of AdaBoost =====
 
 With the above definitions we are now ready to set up the algorithm for AdaBoost.
+The basic idea is to set up weights which will be used to scale the correctly classified and the misclassified cases.
+o We start by initializing all weights to $w_i = 1/n$, with $i=0,1,2,\dots n-1$. It is to see then that $\sum_{i=0}^{n-1}w_i = 1$.
+o We rewrite the misclassification error as 
+!bt
+\[
+\mathrm{err}=\frac{\sum_{i=0}^{n-1}w_iI(y_i\ne G(\bm{X}_{i*})}{\sum_{i=0}^{n-1}w_i},
+\]
+!et