carry more weight means: the coefficient of those features which caused incorrect prediction are increased thus they carry more weight before the model is sent for iteration.

y-h(x) : results in new value of y lets say y’. In case of classification the resultant model will have values of y on either extreme end (depends how many classes we are classifying the problem)