Symposium

Of Rising Scholars

Spring 2024

Lilian will be presenting at The Symposium of Rising Scholars on Saturday, March 23rd! To attend the event and see Lilian's presentation.

Go to Polygence Scholars page
Lilian Pamula's cover illustration
Polygence Scholar2024
Lilian Pamula's profile

Lilian Pamula

Class of 2025Fremont, California

About

Projects

  • "How can random forest regressors be used to better predict how much land a forest fire will burn?" with mentor Kristen (Feb. 28, 2024)

Project Portfolio

How can random forest regressors be used to better predict how much land a forest fire will burn?

Started Dec. 12, 2023

Abstract or project description

Forest fires are a problem which affect many people in various parts of the world, and can cause billions of dollars in damages and take many lives. In the past, it has often been unclear when a forest fire will be contained and how much land it will burn by that point. This paper aims to use random forest regressors to predict how much land will be burned before a fire is put out. A random forest regressor is an algorithm used in machine learning to predict values, and is composed from multiple decision trees. A decision tree asks a series of yes or no questions to determine what prediction best corresponds with a piece of data. This algorithm can be easily interpreted to see which factors most affect the final outcome, which in this case can show which factors will most affect the total area burned by a forest fire.