function [Label, Err] = predAdaBoost(abClassifier, X, Y)

N = size(X, 1);

if nargin < 3

    Y = [];

end

M = abClassifier.nWC;

LabM = zeros(N, M);

for i = 1:M

    LabM(:,i) = abClassifier.Weight(i)*predStump(X, abClassifier.WeakClas{i});

end

% 

Label = zeros(N, 1);

LabM = sum(LabM, 2);

idx = logical(LabM > 0);

Label(idx) = 1;

Label(~idx) = -1;

% 

if ~isempty(Y)

    Err = logical(Label ~= Y);

    Err = sum(Err)/N;

end

end