Machine Learning with R: Random Forest Classification Approach Online
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.
*Presented by Shaila Jamal (DASH Support Assistant). This virtual workshop will be recorded and shared on the Sherman Centre's website.
More information on Sherman Centre Events can be found on the SCDS Events page.
CODE OF CONDUCT
The Sherman Centre and the McMaster University Library are committed to fostering a supportive and inclusive environment for its presenters and participants. As a participant in this session, you agree to support and help cultivate an experience that is collaborative, respectful, and inclusive, as well as free of harassment, discrimination, and oppression. We reserve the right to remove participants who exhibit harassing, malicious or persistently disruptive behaviour. Please refer to our code of conduct webpage for more information.