The Spider Objects

 
 
 
 
   GET_MEAN object   
 


    R=get_mean(A,[L])
   
    An object which calculates the mean(s) R of results with algorithms A,
    together with the standard error (std. dev / sqrt(number of trials))
    optionally calculating the loss with loss type L (see help loss)
    e.g 'class_loss',.. (NOTE: input is a string, not a loss object).
    when trained, e.g:  train(get_mean(cv(svm)),gen(toy))
  
    Hyperparameters:
     take_average=0       -- method of taking average over groups
                             1: average over inside leaf of tree of groups
                             2: average over outside leaf of tree of groups
                             0: try to guess which is most appropriate 
  
          'take_average' is necessary because if you have a group
           of groups of algorithms you could wish to take the mean in two
           different ways: e.g with group({group({a b} group({c d}))}) 
           you may either wish to average a&b and c&d or a&c and b&d.
  
           NOTE: The same effect can usually be achieved by doing
                 get_mean(r) and get_mean(r') with a data object r
     
    Alternatively, can be used in a feed
    forward network, e.g: train(chain({ group(cv(svm)) get_mean }),gen(toy))
    
    Can also be called like a function with 
    A=get_mean(D,[L]) calculates the mean for groups of data objects D.