function [Features] = ...
    kNN_model_load(matFileName)

% This function loads a kNN audio segment classification model
%
% ARGUMENT:
% - matFileName:    the path of the model 
%
% RETURNS:
% - Features:       a cell array that contains the audio features.
%                   e.g. Features{1} contains the features of the 1st class
% - MEAN:           the mean feature vector (to be used for normalization)
% - STD:            the std feature vector
% - stWin, stStep:  short-term window size and step
% - mtWin, mtStep:  mid-term window size and step
%

load(matFileName);
% % [MEAN, STD] = computeMeanStd(Features);
% % Features = normalize(Features, MEAN', STD');
% % 
% % 
% % function Features = normalize(Features, MEAN, STD)
% % 
% % for (i=1:length(Features))
% %     for (j=1:size(Features{i}, 2))        
% %         Features{i}(:,j) = (Features{i}(:,j) -  MEAN) ./ STD;
% %     end
% % end
% % 
% % 
% % function [MEAN, STD] = computeMeanStd(Features)
% % 
% % Fall = [];
% % for (i=1:length(Features)) % for each class dataset:
% %     Fall = [Fall Features{i}];
% % end
% % 
% % MEAN = mean(Fall');
% % STD = std(Fall');