function [net, niter] = logist2FitRegularized(labels, features, maxIter)if nargin < 3, maxIter = 100; end[D  N] = size(features);weightPrior = 0.5;net = glm(D, 1, 'logistic', weightPrior);options = foptions;options(14) = maxIter;[net, options] = glmtrain(net, options, features', labels(:));niter = options(14);%w = logist2Fit(labelsPatches(jValidPatches), features(:, jValidPatches));