<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>

CC BY-SA 4.0
2020-05-12T07:47:05.713Z
2020-05-12T07:47:05.713Z
Fnguyen
<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>

<machine-learning><deep-learning><terminology><cross-validation>
What are non-held-out data or non-held-out classes?
VansFannel
# 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


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## 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.


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