Answers.Body: <p>If you are asking for arbitrary ML task dealing with 1000+ classes the most straigtforward thing that comes to mind is the <code>ImageNet</code> - <a href="https://en.wikipedia.org/wiki/ImageNet#cite_note-nytimes_2012-2" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/ImageNet#cite_note-nytimes_2012-2</a>. It has more the 20k categories in the present time.</p>
  <p>In order to perform such classification task you need</p>
  <ul>
  <li>A large enough dataset, such that each class occurs frequently enough or efficient data augmentation</li>
  <li>A powerful model, such that can adapt to variety of different problems</li>
  </ul>
  <p>The first neural network to tackle this problem was <code>AlexNet</code> and since then plethora of architectures : <code>VGG's</code>, <code>ResNet's</code>, <code>EfficientNet</code> got better and better quality.</p>
  <p>They have a lot of filters that react on different patterns.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-02-03T15:24:59.107Z
Answers.LastActivityDate: 2021-02-03T15:24:59.107Z
Answers.UserDisplayName: spiridon_the_sun_rotator
Body: <p>I am trying to find research paper with theory(preferably implementation) that is about classifying 1000 (or more) classes. I have heard of an implementation, that initially clustering needs to be done then classification with something like softmax. Does anyone know of any research paper that implements 1000+ class classification.</p>
  
Tags: <machine-learning><classification><text-classification>
Title: How to go about classifying 1000 classes?
UserDisplayName: Naveen Reddy Marthala
ThreadText: # How to go about classifying 1000 classes?
  
  (Asked by: username_0 on 2021-02-03)
  
  I am trying to find research paper with theory(preferably implementation) that is about classifying 1000 (or more) classes. I have heard of an implementation, that initially clustering needs to be done then classification with something like softmax. Does anyone know of any research paper that implements 1000+ class classification.
  
  **Tags:** machine-learning, classification, text-classification
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-02-03. Score: 4
  
  If you are asking for arbitrary ML task dealing with 1000+ classes the most straigtforward thing that comes to mind is the `ImageNet` - <https://en.wikipedia.org/wiki/ImageNet#cite_note-nytimes_2012-2>. It has more the 20k categories in the present time.
  
  In order to perform such classification task you need
  
  * A large enough dataset, such that each class occurs frequently enough or efficient data augmentation
  * A powerful model, such that can adapt to variety of different problems
  
  The first neural network to tackle this problem was `AlexNet` and since then plethora of architectures : `VGG's`, `ResNet's`, `EfficientNet` got better and better quality.
  
  They have a lot of filters that react on different patterns.
  
  
  ---
  
  