Machine Learning with R: Random Forest Classification Approach
The Random Forest is a powerful algorithm used for classification in the industry. The classification algorithm consists of many decision trees to get more accurate predictions. This workshop will go over the theoretical part of Random Forest, then provide attendees with hands-on training on conducting Random Forest classification, training the data, testing accuracy, and working with tuning parameters.
A beginner-level understanding of R-programming, introductory statistical knowledge, and familiarity with decision trees are required for this workshop.
Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, Environment, and Society. Book an appointment with Shaila or another member of the DASH Team.
This event is run in collaboration with the YWCA’s Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry.
Workshop Preparation
Preparation for this tutorial consists of two steps: Getting the data and Getting the software. Follow the steps below.
Get the data
Access the files mentioned in the workshop.
Get the software
This hands-on workshop uses R, a software application for data analysis. The program is free to download.