新建 文本文档 (2).txt

偏最小二乘 希望对大家编程有启发-PLS simulation program, we hope to have inspired programming

function [alpha, trainY] = dualPLS(K,Y,T,str)

% PLS Regression & Classificaion algorithm
%
% Usage: [alpha, trainY] = dualPLS(K,Y,T,str)
%
% Inputs:
% K is an (l x l) kernel matrix
% Y is an (l x m) containing the corresponding output vectors
% T gives the number of iterations to be preformed
% str - defines whether it will return the features or for regression
%       input = 'fs' | 'reg'
%
% outputs
% alpha is the regression coefficients
% trainY is the training outputs
%
% David R. Hardoon - [email][e-mail][/email]
% Created - 10/02/04
%
% 31/01/05 - Added some possible bug handling
%
% No commercial use.
% Any modification, please email me a copy.

if (nargin < 4) 
  alpha = 0;
  trainY = 0;
  disp('Please define all inputs');
  help dualPLS;
  return;
end

disp('.... Initialising Data')
% Craig note -- the following two lines should not really be there
% this is for centering in primal space -- however it doesn't actually affect
% as we re-center the kernel matrix later
%mu = mean(K)
disp('.... Initialisation Completed - Entering Algorithm');

for i=1:T
    YYK = YY*YY'*KK;
    beta(:,i) = YY(:,1)/norm(YY(:,1));
    
    if size(YY,2) > 1 % only loop if dimension greater than 1
        bold = beta(:,i) + 1;
        
        while ((norm(beta(:,i) - bold) > 0.001) & (count < 50))
            count = count + 1;
            bold = beta(:,i);
            tbeta = YYK*bold;
            beta(:,i) = tbeta/norm(tbeta);
        end
    end

    tau(:,i) = KK*beta(:,i);
    val = norm(tau(:,i))^2;
    c(:,i) = YY'*tau(:,i)/val;
    
    trainY = trainY + tau(:,i)*c(:,i)';
    trainerror = norm(Y - trainY,'fro')/sqrt(l);
    w = KK*tau(:,i)/val;
    KK = KK - tau(:,i)*w' - w*tau(:,i)'+tau(:,i)*tau(:,i)'*(tau(:,i)'*w)/val;
    YY = YY - tau(:,i)*c(:,i)';
end

if strcmp(str,'fs')
  disp('.... Computing Features');
  alpha = beta*inv(tau'*K*beta)*diag(diag(tau'*tau));
elseif strcmp(str,'reg')
  disp('.... Computing Regression Values')
  alpha = beta*inv(tau'*K*beta)*tau'*Y;
end