datafiles.m

支持向量机工具箱

% DATAFILES describes data files used in the STPR toolbox.
%
% The demo programs and other toolbox functions use two 
% types of data files:
%  1) finite point sets.
%  2) mixture of Gaussians.
%
% The data files can be created by the user program or
% interactively by program 'creatset'.
% 
% 1) Finite point sets: 
% -----------------------------
%  are stored in Matlab file which must contain following variables:
%
%  id [string] string identifier id = 'Finite sets, Enumeration'. 
%              The identification string can be obtaind also by command
%              id=dataid(1).
%  X [NxL]     matrix representing finite point set. The number 
%              of points is L. The points are stored as N-dimensional 
%              column vector, i.e. X = [x1,x2,...,xL].
%  I [1xL]     vector of integers which contains labels for points X.
%              The i-th point X(:,i) has label I(i).
%              Most functions use label 1 for the 1st class, 
%              label 2 for the 2nd class and so on.
%  N [1x1]     data dimension.
%  K [1xM]     contains numbers of points in indicidual classes, 
%              i.e. having the same label. The M is number of classes 
%              (usualy M=max(I)). The integer K(i) is number
%              of points which belong to the i-th class, i.e. 
%              the number of points which have label=i. 
%  
% Example:  
%  id = dataid(1);                 % or id = 'Finite sets, Enumeration'.
%  X = [[0;0],[1;0],[0;1],[1;1]];  % logical AND.
%  I = [ 1      2     2     2  ];  % labels.
%  N = 2;                          % dimension is also size(X,1);
%  K = [1,3];                      % also K(1)=length(find(I==1)),
%                                  %      K(2)=length(find(I==2)) and
%                                  % sum(K) == size(X,2);
% 
% 2) Mixture of Gaussians:
% ----------------------------------
%  is stored in Matlab file which must contain following variables:
%
%  id [string] string identifier id = Infinite sets, Normal distributions'. 
%              The identification string can be obtaind also by command
%              id=dataid(2).
%  MI [NxL]    matrix which contains mean vectors. The number 
%              of points is L. The mean vector are stored as N-dimensional 
%              column vector, i.e. MI = [mi1,mi2,...,miL].
%  SIGMA [Nx(L*N)] matrix which contains covariance matrices. The number 
%              of matrices is L. The matrices are store one by one, i.e.
%              SIGMA =[sigma1,sigma2,...,sigmaL], where sigmai is i-th
%              covariance matrix. To take i-th matrix use command
%              acov(SIGMA,i).
%  I [1xL]     vector of integers which contains labels. The i-th
%              Gaussian represented by the mean vector MI(:,i) and
%              covariance matrix acov(SIGMA,i) has label I(i).
%  N [1x1]     data dimension.
%  K [1xM]     contains numbers of Gaussians in individual classes, 
%              i.e. having the same label. The M is number of classes.
%              The integer K(i) is number of Gaussians which have label i.
% 
% Example:
%  id = dataid(1);             % or id = 'Infinite sets, Normal distributions'.
%  MI = [[-1;-1],[1;1]];       % two Gaussians with mean vectors [-1;-1],[1;1]
%  SIGMA = [eye(2,2),eye(2,2)] % and identity covariance matrices.
%  I =  [ 1      2];           % labels.
%  N = 2;                      % dimension is also size(MI,1) == size(SIGMA,1);
%  K = [1,1];                  % also K(1)=length(find(I==1)),
%                              % K(2)=length(find(I==2)) and
%                              % sum(K) == size(MI,2)
%
% See also CHECKDAT, DATAID, CREATSET.
%

% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 02.01.2000
% Modifications
% 26-June-2001, V.Franc, created.