Iterative_Input_Selection/perform_IIS.m at master · Critical-Infrastructure-Systems-Lab/Iterative_Input_Selection · GitHub

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function result = perform_IIS(data,M,nmin,ns,p,epsilon,max_iter,Vflag,verbose)

% This function is a wrapper around iterative_input_selection.m,
% the function implementing the IIS technique using Extra-Trees.
%
%
% data              = dataset;
%
% rtensparam        = extra-trees parameters;
%
% ns                = number of folds for cross validation;
%
% p                 = number of SISO models evaluated at each iteration
%                    (this number must be smaller than the number of
%                     candidate inputs);
%
% epsilon           = tolerance;
%
% max_iter          = maximum number of iterations;
%
% verbose           = 0 for silent run. 1 for verbose mode
%
% Vflag     = selection of the type of validation,
%               1 = k-fold(default)
%               2= repeated random sub-sampling
%
% Outputs
% result   = structure containing the result for each iteration
% LOG      = the original algorithm printout saved to text


% 0) check if p <= number of attributes
natt = size(data,2)-1;

if p > natt
    error(['The number of SISO models evaluated',...
        'has to be < number of candidate inputs'])
end

% 1)  Launch IIS algorithm

% Shuffle the data
data_sh = shuffle_data(data);

% Run the IIS algorithm
if verbose == 0
    evalc('result = iterative_input_selection(data_sh,M,nmin,ns,p,epsilon,max_iter,Vflag)');
else
    result = iterative_input_selection(data_sh,M,nmin,ns,p,epsilon,max_iter,Vflag);
end


% This code has been written by Riccardo Taormina.