Answers.Body: <p>Of course. It only depends if those features are informative enough for the task at hand. In order to better understand the phenomenon, you can imagine 2 features displayed as points in a 2D plane. The number of possible target classes goes up to the number of clusters you can find in that plane.</p>
  
  <p>About the suggestion, I can only recommend the utilisation of a non-linear classifier.</p>
  
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Answers.CreationDate: 2019-11-26T16:13:16.347Z
Answers.LastActivityDate: 2019-11-26T16:13:16.347Z
Answers.UserDisplayName: David
Body: <p>Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I have 2000 target variables?</p>
  
Tags: <machine-learning><classification>
Title: Can I perform multiclass classification when the number of features is less than the number of targets?
UserDisplayName: ATidedHumour
ThreadText: # Can I perform multiclass classification when the number of features is less than the number of targets?
  
  (Asked by: username_0 on 2019-11-26)
  
  Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I have 2000 target variables?
  
  **Tags:** machine-learning, classification
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-11-26. Score: 2 | Accepted answer
  
  Of course. It only depends if those features are informative enough for the task at hand. In order to better understand the phenomenon, you can imagine 2 features displayed as points in a 2D plane. The number of possible target classes goes up to the number of clusters you can find in that plane.
  
  About the suggestion, I can only recommend the utilisation of a non-linear classifier.
  
  
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