data_load(id,sw,nk,N2,type)

function [data, N1, N, Ns, truelabels, dc] = data_load(id,sw,nk,N2,type)

data = load(sw);
[nrow, dim] = size(data);
N1=2; 
N = max([N2,nk+6]);     % searching limit at k = N
Ns = N1:N;
truelabels = ones(nrow,1);
if id < 21                       % when 1st column is class labels
   truelabels = data(:,1);
   data = data(:,2:dim);
  % dim = dim-1;
  % datasort_bylabel
end
dc = 2;

if id == 22
  % remove half of cancer & normal tissures closer to each other under Euclidean metric
  Dist= similarity_euclid(data');
  cancers = [1,3,5,7,9,11,13,15,17,19,21,23,25,26,27,28,29,30,31,32,...
      33,34,35,36,37,38,40,41,44,45,46,47,49,52,53,56,57,58,59,61];
  normals = [2,4,6,8,10,12,14,16,18,20,22,24,39,42,43,48,50,51,54,55,60,62];
  [A1,B1] = findnear(Dist,normals',11,cancers',20,2);
  A1 = setdiff(normals,A1);
  B1 = setdiff(cancers,B1);
  data = data(:,[A1 B1]);
end