title: Feature importance with keras
body: <p>i have the following question. I created a neural network with Keras. That is a <strong>Part</strong> of my dataFrame.
  My DataFrame looks like:</p>
  
  <pre><code>    Id          MainCl   Class     Other Options...
      1016178069  0        30        1              
      1016178012  0        25        0              
  </code></pre>
  
  <p>My result vector gives me the probability in which class the result can be classified.
  Example:</p>
  
  <pre><code>Prob_isClass_A    Prob_isClass_b
  0.756686          0.243314
  0.999843          0.000157006
  0.999818          0.000182159
  </code></pre>
  
  <p>Now to the main question: 
  Is there a way to get the highest probability of a feature that is responsible for the result?
  Like:</p>
  
  <pre><code>Prob_isClass_A    Prob_isClass_b      Most_Probability_Reason    Probability
  0.756686          0.243314            Main_CL_Feature            0.75
  0.999843          0.000157006         Class_Feature              0.8
  0.999818          0.000182159         Other_Option_Feature       0.7
  </code></pre>