qmf = [1,1]/sqrt(2); % Haar Wavelet
    L   = 3;             % # Levels in the pyramid
    W   = fwtn(X,L,qmf); % apply FWT, inverse: X = fwtn(W,L,qmf,1);

    lhyp = [1; 1];      % ell,sig - GP parameters
    cov  = {'covSEiso'};% covariance function
    lik  = 'cumGauss';  % logistic or cumGauss likelihood
    apx  = 'LA';        % EP,FV,IVM,KL,LA,LR,OLEP,SO,TAP,TAPnaive or VB
    p = binaryGP(lhyp, ['approx',apx], cov, lik, x, y, xtest); % prediction