Answers.Body: <p>Held-out simply means "not included" particularly in the sense of:</p>
  
  <p><strong>This part of the data was not included in this specific training run.</strong></p>
  
  <p>Depending on the context of all of these text <strong>non-held-out data/classes means the data that actually was included in a particular modeling exercise.</strong></p>
  
  <p>Consider this excerpt from your first example:</p>
  
  <blockquote>
    <p>For instance, Owen and Perry (2009) show a method for <strong>holding out data</strong>, computing SVD on the <strong>non-held-out data</strong>, and selecting k so as to minimize the reconstruction error between the <strong>held-out data</strong> and its SVD approximation.</p>
  </blockquote>
  
  <p>It actually means:</p>
  
  <blockquote>
    <p>For instance, Owen and Perry (2009) show a method for <strong>excluding data</strong>, computing SVD on the <strong>remaining data</strong>, and selecting k so as to minimize the reconstruction error between the <strong>excluded data</strong> and its SVD approximation.</p>
  </blockquote>
  
  <p>So it simply talks about a particular way of train-test-validation splitting the data.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-05-12T07:47:05.713Z
Answers.LastActivityDate: 2020-05-12T07:47:05.713Z
Answers.UserDisplayName: Fnguyen
Body: <p>I'm Spanish and I don't understand the meaning of "non-held-out". I have tried Google Translator and online dictionaries like Longman but I can't find a suitable translation for this term.</p>
  
  <p>You can find these term using this <a href="https://www.google.com/search?client=firefox-b-d&amp;biw=1920&amp;bih=901&amp;ei=WUe6XtOICaqIlwTQ8Yy4BA&amp;q=%22non-held-out%22%20meaning&amp;oq=%22non-held-out%22%20meaning&amp;gs_lcp=CgZwc3ktYWIQDFAAWABghCBoAHAAeACAAQCIAQCSAQCYAQCqAQdnd3Mtd2l6&amp;sclient=psy-ab&amp;ved=0ahUKEwiTmcCZ3q3pAhUqxIUKHdA4A0c4ChDh1QMICw" rel="nofollow noreferrer">Google Search</a>, and in articles like this one:</p>
  
  <ol>
  <li>"<strong>computing SVD on the non-held-out data</strong>" from <a href="https://link.springer.com/article/10.1007/s10618-019-00616-4" rel="nofollow noreferrer">here</a>.</li>
  <li>"<strong>The training set consists all the images and annotations containing non-held-out classes while held-out classes are masked as background during the training</strong>" from <a href="http://bmvc2018.org/contents/papers/0255.pdf" rel="nofollow noreferrer">Few-Shot Semantic Segmentation with Prototype Learning</a>.</li>
  <li>"<strong>A cross-validation procedure is that non held out data (meaning after holding out the test set) is splitted in k folds/sets</strong>" from <a href="https://datasciencelab.its.uconn.edu/cross-validation/" rel="nofollow noreferrer">here</a>.</li>
  </ol>
  
  <p>What is non-held-out data and held-out data or classes?</p>
  
Tags: <machine-learning><deep-learning><terminology><cross-validation>
Title: What are non-held-out data or non-held-out classes?
UserDisplayName: VansFannel
ThreadText: # What are non-held-out data or non-held-out classes?
  
  (Asked by: username_0 on 2020-05-12)
  
  I'm Spanish and I don't understand the meaning of "non-held-out". I have tried Google Translator and online dictionaries like Longman but I can't find a suitable translation for this term.
  
  You can find these term using this [Google Search](https://www.google.com/search?client=firefox-b-d&biw=1920&bih=901&ei=WUe6XtOICaqIlwTQ8Yy4BA&q=%22non-held-out%22%20meaning&oq=%22non-held-out%22%20meaning&gs_lcp=CgZwc3ktYWIQDFAAWABghCBoAHAAeACAAQCIAQCSAQCYAQCqAQdnd3Mtd2l6&sclient=psy-ab&ved=0ahUKEwiTmcCZ3q3pAhUqxIUKHdA4A0c4ChDh1QMICw), and in articles like this one:
  
  1. "**computing SVD on the non-held-out data**" from [here](https://link.springer.com/article/10.1007/s10618-019-00616-4).
  2. "**The training set consists all the images and annotations containing non-held-out classes while held-out classes are masked as background during the training**" from [Few-Shot Semantic Segmentation with Prototype Learning](http://bmvc2018.org/contents/papers/0255.pdf).
  3. "**A cross-validation procedure is that non held out data (meaning after holding out the test set) is splitted in k folds/sets**" from [here](https://datasciencelab.its.uconn.edu/cross-validation/).
  
  What is non-held-out data and held-out data or classes?
  
  **Tags:** machine-learning, deep-learning, terminology, cross-validation
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-05-12. Score: 1 | Accepted answer
  
  Held-out simply means "not included" particularly in the sense of:
  
  **This part of the data was not included in this specific training run.**
  
  Depending on the context of all of these text **non-held-out data/classes means the data that actually was included in a particular modeling exercise.**
  
  Consider this excerpt from your first example:
  
  > For instance, Owen and Perry (2009) show a method for **holding out data**, computing SVD on the **non-held-out data**, and selecting k so as to minimize the reconstruction error between the **held-out data** and its SVD approximation.
  
  It actually means:
  
  > For instance, Owen and Perry (2009) show a method for **excluding data**, computing SVD on the **remaining data**, and selecting k so as to minimize the reconstruction error between the **excluded data** and its SVD approximation.
  
  So it simply talks about a particular way of train-test-validation splitting the data.
  
  
  ---
  
  