title: How to determine unknown class in image classification model such as mobilenet?
body: <p>I have <code>n</code> classes and a one <code>unknown</code>. </p>
  
  <p><code>Unknown</code> is not included in the training set as the way is not explored as yet by me.</p>
  
  <p>I trained the mobilenet(or inception-v3) for <code>n</code> classes. The confusion matrix is very good.</p>
  
  <p>Now if an <code>unknown-class</code> image comes in for prediction, the model predicts it as any of the n classes. <code>Which is clearly misclassified</code>. </p>
  
  <p>The confidence also comes near by <code>0.998</code>, which makes it difficult to filter out. Otherwise known class object of n trained classes is classified at same confidence.</p>
  
  <p>I tried keeping a class which does not include any feature set of n classes i.e. sort of negative sampled class as unknown class. As output, the confusion matrix goes very bad. Bad enough not to go further with that. This I am still going through.</p>
  
  <p>How to determine unknown class using neural network? That it doesn't fall in any known class classification.</p>