Answers.Body: <p>Have you tried google searching? There are many results that come up for "multi-label k nearest neighbor image classification". Here are the first couple of papers to get you started:</p>
  
  <p><a href="http://proceedings.mlr.press/v25/chiang12/chiang12.pdf" rel="nofollow noreferrer">http://proceedings.mlr.press/v25/chiang12/chiang12.pdf</a>
  <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.86.9501&amp;rep=rep1&amp;type=pdf" rel="nofollow noreferrer">http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.86.9501&amp;rep=rep1&amp;type=pdf</a></p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-07-18T18:58:50.047Z
Answers.LastActivityDate: 2017-07-18T18:58:50.047Z
Answers.UserDisplayName: Adam
Body: <p>I'm not quite sure how I should go about creating a multi-label image KNN classifier using python as a lot of the literature I have read does not explicitly explain this methodology. Specifically, I am not sure how I would be able to potentially yield multiple labels per image using the KNN classifier architecture. Any insight would be greatly appreciated! (new to coding by the way)</p>
  
Tags: <classification>
Title: Multi-Label Image Classification using KNN
UserDisplayName: Richard Kim
ThreadText: # Multi-Label Image Classification using KNN
  
  (Asked by: username_0 on 2017-07-11)
  
  I'm not quite sure how I should go about creating a multi-label image KNN classifier using python as a lot of the literature I have read does not explicitly explain this methodology. Specifically, I am not sure how I would be able to potentially yield multiple labels per image using the KNN classifier architecture. Any insight would be greatly appreciated! (new to coding by the way)
  
  **Tags:** classification
  
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  ## 1 answers
  
  ### Answer by username_1 on 2017-07-18. Score: 1
  
  Have you tried google searching? There are many results that come up for "multi-label k nearest neighbor image classification". Here are the first couple of papers to get you started:
  
  <http://proceedings.mlr.press/v25/chiang12/chiang12.pdf>
  <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.86.9501&rep=rep1&type=pdf>
  
  
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