Answers.Body: <p>They are equivalent. When we consider a particular instance as a vector, we are not literally imagining it as an arrow with it's head at the point coordinates and tail at the origin. It's just when you are working with a tuple of numbers in a mathematical context, it is conventional to call it a vector. This language follows into machine learning which is usually based on associated linear algebra.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-10-27T07:00:31.463Z
Answers.LastActivityDate: 2020-10-27T07:00:31.463Z
Answers.UserDisplayName: Cameron Chandler
Body: <p>Across the literature of artificial intelligence, especially machine learning, it is normal to treat the tuples of datasets as vectors.</p>
  <p>Although there is a convention to treat them as data points. Treating them as vectors is also considerable.</p>
  <p>It is easy to understand the tuples of datasets as points over space. But what is the purpose of treating them as vectors?</p>
  
Tags: <machine-learning><terminology><datasets><vectors>
Title: What is the reason for taking tuples as vectors rather than points?
UserDisplayName: hanugm
ThreadText: # What is the reason for taking tuples as vectors rather than points?
  
  (Asked by: username_0 on 2020-10-27)
  
  Across the literature of artificial intelligence, especially machine learning, it is normal to treat the tuples of datasets as vectors.
  
  Although there is a convention to treat them as data points. Treating them as vectors is also considerable.
  
  It is easy to understand the tuples of datasets as points over space. But what is the purpose of treating them as vectors?
  
  **Tags:** machine-learning, terminology, datasets, vectors
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-10-27. Score: 4
  
  They are equivalent. When we consider a particular instance as a vector, we are not literally imagining it as an arrow with it's head at the point coordinates and tail at the origin. It's just when you are working with a tuple of numbers in a mathematical context, it is conventional to call it a vector. This language follows into machine learning which is usually based on associated linear algebra.
  
  
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