var data = csv.read('test-cnn-DT.csv'),
    x,
    y;

data.shift();
x=select(data,0,data[0].length-2);
y=select(data,data[0].length-1);


var model = ml.learn({
  algorithm:ml.ML.CNN,
  x:x,  // [row1=[col1=[z1,z2,..],col2,..],row2,..]
  y:y,
  width:28,
  height:28,
  depth:1,
  normalize:[-.5,.5],
  iterations:100,
  layers:[
    // output Vol is of size 3x4x2 here
    {type:'input', out_sx:28, out_sy:28, out_depth:1},
    {type:'conv', sx:5, filters:8, stride:1, pad:2, activation:'relu'},
    {type:'pool', sx:2, stride:2},
    {type:'conv', sx:5, filters:16, stride:1, pad:2, activation:'relu'},
    {type:'pool', sx:3, stride:3},
    {type:'softmax', num_classes:10}
  ],
  trainer : {method: 'adadelta', 
            l2_decay: 0.001, 
            batch_size: 10}
});
// print(model)
for(var i=0;i<100;i++)
  print(y[i],ml.stats.utils.best(ml.classify(model,x[i]).w))