text: /**
   * Created by joonkukang on 2014. 1. 15..
   */
  var dnn = require('../lib/dnn');
  var x = [[1,1,1,0,0,0],
      [1,0,1,0,0,0],
      [1,1,1,0,0,0],
      [0,0,1,1,1,0],
      [0,0,1,1,0,0],
      [0,0,1,1,1,0]];
  var y = [[1, 0],
      [1, 0],
      [1, 0],
      [0, 1],
      [0, 1],
      [0, 1]];
  
  var pretrain_lr = 0.6, pretrain_epochs = 900, k = 1, finetune_lr = 0.6, finetune_epochs = 500;
  
  var dbn = new dnn.DBN({
      'input' : x,
      'label' : y,
      'n_ins' : 6,
      'n_outs' : 2,
      'hidden_layer_sizes' : [10,12,11,8,6,4]
  });
  
  dbn.set('log level',1);
  
  // Pre-Training using using RBM
  dbn.pretrain({
      'lr' : pretrain_lr,
      'k' : k,
      'epochs' : pretrain_epochs
  });
  
  // Fine-Tuning dbn using mlp backpropagation.
  dbn.finetune({
      'lr' : finetune_lr,
      'epochs' : finetune_epochs
  });
  
  x = [[1, 1, 0, 0, 0, 0],
      [0, 0, 0, 1, 1, 0],
      [1, 1, 1, 1, 1, 0]];
  
  console.log(dbn.predict(x));