normalize_feature.m

function [feature, normalize_ratio]= normalize_feature(feature,normalize_ratio)
%
% Ratio = 0
% normalize each dimension of the feature seperately for L2 regularized
% logistic regression.
% Record the parameter of each dimension in the global variable.
% given normalize_ratio
% compute normalized feature according to ratio
%
num_dim = size(feature,2);

% compute and record ratio and normalized feature
if nargin ==1
    normalize_ratio = zeros(num_dim,2);
    for i = 1 : num_dim
        fprintf('normalize for dimention %d. \n', i);
        v = feature(:,i);
        v_min = min(v);
        v_max = max(v);
        if v_max - v_min ~=0
            v_new = (v - v_min)/(v_max - v_min);
        else
            v_new = v;
        end
        % normalized feature
        feature(:,i) = v_new;
        
        % normalize ratio
        normalize_ratio(i,:) = [v_min v_max];
    end
    % compute normalized feature
elseif nargin ==2
    for  i = 1 : num_dim
        v_min = normalize_ratio(i,1);
        v_max = normalize_ratio(i,2);
        if v_max - v_min ~=0
            feature(:,i) = (feature(:,i) - v_min)./(v_max - v_min);
        else
            feature(:,i) = feature(:,i);
        end
    end
end
end