wolffd@0: function [net, niter] = logist2FitRegularized(labels, features, maxIter)
wolffd@0: 
wolffd@0: if nargin < 3, maxIter = 100; end
wolffd@0: 
wolffd@0: [D  N] = size(features);
wolffd@0: weightPrior = 0.5;
wolffd@0: net = glm(D, 1, 'logistic', weightPrior);
wolffd@0: options = foptions;
wolffd@0: options(14) = maxIter;
wolffd@0: [net, options] = glmtrain(net, options, features', labels(:));
wolffd@0: niter = options(14);
wolffd@0: %w = logist2Fit(labelsPatches(jValidPatches), features(:, jValidPatches));
wolffd@0: