title: How do I perform multi layer classification?
body: <p>In my dataset, I explored there are actually <strong>three layers</strong> of labels. All are not independent labels. For the first layer, the label is binary. If the class is 1, we can go to the further layer. The second layer has four different class and each class can belong to 42 different classes. In a nutshell, the class or labels are in a tree. Now I want to perform a classification to find out all three layers of labels in a single experiment.</p>
  
  <p>This image <a href="https://drive.google.com/file/d/1M8yVI7mMBa9Wr9q7UQQZQ-X3q9MBDGaT/view?usp=sharing" rel="nofollow noreferrer">https://drive.google.com/file/d/1M8yVI7mMBa9Wr9q7UQQZQ-X3q9MBDGaT/view?usp=sharing</a> shows the layers of labels. </p>
  
  <p>I want to classify if a given data is malware or not. If it is malware, I want to find out its category and which family it belongs to. I want to do all these in a single process. I heard about scikit multi-label classification, but I am not sure if it is really a multi-label classification problem.</p>