Problem $4($AdaBoosting$)(1\%)$

Consider training an Adaboosting classifier using decision stumps on the data set illustrated in Figure $1$:

Figure $1$: AdaBoost Data set

$($a$)$ Which examples will have their weights increased at the end of the first iteration? Circle them.

$($b$)$ How many iterations will it take to achieve zero training error? Justify your answers and show each iteration step.

$2.$ Suppose AdaBoost is run on $N$ training examples, and suppose on each round that the weighted training error $lo{n}_t$ of the $t^{\text{'}}$ th weak hypothesis is at most $\frac{1}{2}-,$ for some number After how many iterations, $T,$ will the combined hypothesis be consistent with the $N$ training examples, i$.$e$,$ achieves zero training error? Your answer should only be expressed in terms of $N$ and $.($Hint: Recall that exponential loss is an upper bound for $0-1$ loss. What is the training error when $1$ example is misclassified?$)$