The AdaBoost algorithm states that it is to train a classifier based on the training data according to a weight vector.
Assume the size of training data is N, the weight vector is of dimension N as well. I have three questions regarding this sampling procedure,
1) Will the size of sampled data be the same as the original data set? 2) What does the weight vector look like? If it is a distribution, then the sum of them has to be 1. Is that possible to have a weight vector with entries of integer number? 3) Generally, which algorithm can be used to sample a data set based on a given weight vector or a distribution?