Answers.Body: <p>For any model that does not take a time series approach like an RNN does, the padding shouldn't make a difference.</p>
  <p>I prefer padding right simply because there also might be text you need to cut-off. Then padding is more intuitive as you either cut-off a text if it's too long or pad a text when it's too short.</p>
  <p>Either way, when a model is trained a certain way, it shouldn't make a difference so long the testing is also padded the way it was presented in training.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-03T07:47:33.407Z
Answers.Text: the problem with padding right is the last value for time of RNN unit is mostly always zero, i tackle it by return sequence from the recurrent layer, so it's not affected by the last zero pad. supposed to be correct?
Answers.UserDisplayName: Dan D.
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-03T07:35:07.677Z
Answers.LastActivityDate: 2020-07-03T07:35:07.677Z
Answers.UserDisplayName: N. Kiefer
Body: <p>Text classification of equal length texts works without padding, but in reality, practically, texts never have the same length.</p>
  <p>For example, spam filtering on blog article:</p>
  <pre><code>thanks for sharing    [3 tokens] --&gt; 0 (Not spam)
  this article is great [4 tokens] --&gt; 0 (Not spam)
  here's &lt;URL&gt;          [2 tokens] --&gt; 1 (Spam)
  </code></pre>
  <p>Should I pad the texts on the right:</p>
  <pre><code>thanks for     sharing --
  this   article is      great
  here's URL     --      --
  </code></pre>
  <p>Or, pad on the left:</p>
  <pre><code>--   thanks  for    sharing
  this article is     great
  --   --      here's URL
  </code></pre>
  <p>What are the pros and cons of either pad left or right?</p>
  
Tags: <natural-language-processing><long-short-term-memory><sequence-modeling><text-classification><padding>
Title: Text classification of non-equal length texts, should I pad left or right?
UserDisplayName: Dan D.
ThreadText: # Text classification of non-equal length texts, should I pad left or right?
  
  (Asked by: username_0 on 2020-07-03)
  
  Text classification of equal length texts works without padding, but in reality, practically, texts never have the same length.
  For example, spam filtering on blog article:
  thanks for sharing    [3 tokens] --> 0 (Not spam)
  this article is great [4 tokens] --> 0 (Not spam)
  here's           [2 tokens] --> 1 (Spam)
  
  Should I pad the texts on the right:
  thanks for     sharing --
  this   article is      great
  here's URL     --      --
  
  Or, pad on the left:
  --   thanks  for    sharing
  this article is     great
  --   --      here's URL
  
  What are the pros and cons of either pad left or right?
  
  **Tags:** natural-language-processing, long-short-term-memory, sequence-modeling, text-classification, padding
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-07-03. Score: 1 | Accepted answer
  
  For any model that does not take a time series approach like an RNN does, the padding shouldn't make a difference.
  
  I prefer padding right simply because there also might be text you need to cut-off. Then padding is more intuitive as you either cut-off a text if it's too long or pad a text when it's too short.
  
  Either way, when a model is trained a certain way, it shouldn't make a difference so long the testing is also padded the way it was presented in training.
  
  > **Comments:**
  > **username_0**: the problem with padding right is the last value for time of RNN unit is mostly always zero, i tackle it by return sequence from the recurrent layer, so it's not affected by the last zero pad. supposed to be correct?  
  
  ---
  
  