contents.m

MATLAB的SVM算法实现

% Support Vector Machine Toolbox
% Version 2.0-Aug-1998  
%
% Support Vector Classification
%
%   svc          - Calculate support vectors for classification
%   svcplot      - Plot 2 dimensional classification problem
%   svcoutput    - Calculate output from input data 
%   svcerror     - Calculate error from input and output data 
%   uiclass      - graphical user interface for classification
%
% Support Vector Regression
%
%   svr          - Calculate support vectors for regression
%   svrplot      - Plot 1 dimensional regression problem
%   svroutput    - Calculate output from input data 
%   svrerror     - Calculate error from input and output data 
%   uiregress    - graphical user interface for regression
%
% Kernel function
%
%   svkernel     - kernel function
%   nobias       - determine if kernel has no implicit bias
%   svdatanorm   - Normalise data to appropriate interval for kernel
%
% __________________________________________________________________
%
%  Steve Gunn ([e-mail])
%  Image Speech and Intelligent Systems Group
%  University of Southampton