# Linear functional boosting scores

**URL:** <https://discuss.elastic.co/t/linear-functional-boosting-scores/301844>\
**Category:** Elastic Search\
**Tags:** elastic-app-search\
**Created:** [April 7, 2022, 8:48am UTC](https://discuss.elastic.co/t/linear-functional-boosting-scores/301844 "2022-04-07T08:48:02Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![jsandeep316](https://avatars.discourse-cdn.com/v4/letter/j/e47c2d/32.png) [@jsandeep316](https://discuss.elastic.co/u/jsandeep316)\
**Post date:** [April 7, 2022, 8:48am UTC](https://discuss.elastic.co/t/linear-functional-boosting-scores/301844/1 "2022-04-07T08:48:02Z")

</div>

I'm trying to understand the scoring for linear functional boosts in Elastic App Search.

It says the factor field can range from 0 to 10, defaulting to 1. It also says "A negative factor or fractional factor will not deboost a result.".

Firstly, if the factor can only range from 0 to 10, I don't know why the documentation is talking about a negative factor.

Secondly, and more importantly, I would like to know what the calculation behind the scenes is. For example, if I have Document A with a field, say **Visitors = 10** , and a Document B, with **Visitors = 100** , and I apply a linear functional boost of 0.2, then what is the Boost Value of each document, which is to be combined with the Original Document Score? And how is this Boost Value arrived at, for each of the documents?

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [May 5, 2022, 8:48am UTC](https://discuss.elastic.co/t/linear-functional-boosting-scores/301844/2 "2022-05-05T08:48:07Z")

</div>

This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.