SPIDER The Spider Objects

ADABOOST


    
    
   A=ADABOOST(C,H) returns a template object initialized with learning algorithm C and hyperparameters H. 
  
    The template object is a simple linear support vector machine, with
     soft margin hyperparameter C. Please use this template to
     implement your own algorithms.
  
   Hyperparameters, and their defaults
   kmax = 5                -- number of weak learners
  
   Methods:
    train, test
  
   Model:
    child                  -- learning algorithm
   Example:
  
     Use adaboost with 1-knn as weak learner and validate with 2 fold cross validation.
   c1=[2,0];
   c2=[-2,0];
   X1=randn(50,2)+repmat(c1,50,1);
   X2=randn(50,2)+repmat(c2,50,1);
   
   d=data([X1;X2],[ones(50,1);-ones(50,1)]);
   [r,a]=train(cv(adaboost(knn),'folds=2'),d);
  

Reference : The boosting approach to machine learning: An overview
Author : Robert E. Schapire
Link : http://www.cs.princeton.edu/~schapire/uncompress-papers.cgi/msri.ps