---
title: "A Subtle Bias that Could Impact Your Decision Trees and Random Forests"
url: https://daily.dev/posts/a-subtle-bias-that-could-impact-your-decision-trees-and-random-forests-uwmnnkxoj
source_url: https://towardsdatascience.com/a-subtle-bias-that-could-impact-your-decision-trees-and-random-forests-3480756f7552
type: article
source: "Towards Data Science"
published: 2024-01-02T01:56:55.625Z
updated: 2024-01-02T01:56:53.478Z
tags: ["machine-learning", "random-forest", "decision-tree"]
reading_time: 10
upvotes: 1
comments: 0
language: en
---

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# A Subtle Bias that Could Impact Your Decision Trees and Random Forests

**[Towards Data Science](https://daily.dev/sources/tds)** · 10 min read · 1 upvotes · 0 comments

## Summary

This post discusses a subtle bias that can impact decision trees and random forests. The bias can be eliminated by integrating out the effect of the choice of conditioning operators. The bias is more likely to occur when a feature domain contains highly probable equidistant values and when relatively deep trees are built. Integrating out the bias involves building two forests of half the size, fitting one to the original data and the other to the mirrored data, and averaging the results.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/a-subtle-bias-that-could-impact-your-decision-trees-and-random-forests-3480756f7552>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#random-forest](https://daily.dev/tags/random-forest), [#decision-tree](https://daily.dev/tags/decision-tree)

[View this post on daily.dev](https://daily.dev/posts/a-subtle-bias-that-could-impact-your-decision-trees-and-random-forests-uwmnnkxoj)