title: Bag of words training samples
body: <p>I have implemented Bag Of Words, everything is working smoothly. But, I'm confused about some steps and how to implement it.</p>
  
  <p>I could create the bow descriptors as the last step in Bag of words to create the samples, as it shown here <code>bowDE.compute(img, keypoints, bow_descriptor);</code> .. The things is that i'm confused about the next steps. </p>
  
  <p>I know that in BOW that I have to train and test a class (car) with non-class (cola), what I created in bow_descriptor vector  is only for the class car, so I have vector for samples that belong only to the car. here are the questions that I have for training my system and test it.</p>
  
  <p>1- Shall I make the vector of bow_descriptor half of it for the class(cola) and the rest for non-class(cola) , or I have to create a new bow_descriptor for the non-class(cola) ?</p>
  
  <p>2- I need to do multi-class classification, after finishing the first system for class (car), and I need to train a new class (Buses+trains and so on), shall I create a new training model for each of them, or 
  it is possible to do the training procedure with the previous training (i.e. training class BUS,train with the class car in the same system)?  </p>