title: How to perform a Multi-Class classification in a convoluted neural 1D network with tensorflow?
body: <p>I have a training file in the following format:</p>
  
  <blockquote>
    <p>0.086, 0.4343, 0.4212, ...., class1</p>
    
    <p>0.086, 0.4343, 0.4212, ...., class2</p>
    
    <p>0.086, 0.4343, 0.4212, ...., class5</p>
  </blockquote>
  
  <p>Where, each row is a one-dimensional vector and the last column is the class in which that vector represents. We can see that a vector repeats itself several times, since it has several classes.</p>
  
  <p>Reading this data is done by the python "Panda" library.
  That said, I need to conduct training with a convolutional network. I already researched some sites and did not get much success and also do not know if the network needs to be prepared for the "Multi-Class" form.</p>
  
  <p>I would like to know if someone knows a multi-class 1D classification approach with tensorflow or could guide me with an example, being that after training the network, I need to pass a template (which would be a vector) and the network output me Give the correct percentage of each class.</p>
  
  <p>Thank you!</p>