##  [Random Forest](/index.php/random-forest) 

  ##  [Random Forest](https://natural.quantumdictionary.io/random-forest-0) 

  

 [![Natural & Formal Sciences Dictionary](/sites/default/files/styles/large/public/2026-01/Natural%20%26%20Formal%20Sciences.png.webp?itok=2kCDRVQv)](/index.php/topic-specific-dictionaries/natural-formal-sciences)



**Natural & Formal Sciences Dictionary**

 







 

 

 

 



 

 

 

 

Definition

A supervised learning ensemble method that builds an aggregation of decision trees trained on independent bootstrap-style samples and randomized feature subsets at each split; predictions are formed by majority vote for classification or by averaging for regression.

 

 

 

 

 





 

 



 ##  [Random Forest](https://defense.quantumdictionary.io/random-forest-1) 

  

 [![Defense, Security & Public Safety Dictionary](/sites/default/files/styles/large/public/2026-01/Defense%2C%20Security%20%26%20Public%20Safety.png.webp?itok=3-v4M7xK)](/index.php/topic-specific-dictionaries/defense-security-public-safety)



**Defense, Security & Public Safety Dictionary**

 







 

 

 

 



 

 

 

 

Definition

An ensemble supervised machine‑learning method that builds many decision trees on bootstrap samples and aggregates their predictions (majority vote for classification, average for regression), introducing random feature selection at splits to decorrelate trees and reduce variance relative to single trees.