Classification and Regression Trees and Random Forests with R

Tue, May 26, 2020 10:00 AM - Wed, May 27, 2020 11:30 AM at Zoom

Machine learning is a powerful branch of data science that uses data-driven approaches and statistical methods to derive patterns and make predictions. In this workshop you will learn the fundamentals of two key methods: classification and regression trees (CART) and random forests. Further, you will see how to use these methods in the R environment, and you will have time to experiment with them on multivariate data.

This two-session hands-on workshop will consist of some theory and some practice. You will leave the workshop with a basic understanding of the machine learning model-building practice of training and testing, as well as tools for assessing model performance and interpreting results.

Participants should have some formal training in statistics – if you have applied regression analysis, you should be set on theory for this workshop. In addition you should have some background using R for basic data analysis and be comfortable running scripts and portions of scripts in an R environment such as R-Studio.

• Time: 10A.M. - 11:30A.M., May 26 & 27, 2020 (Tu.&W.)
• Registration: RSVP by May 25, 2020 (Monday)
• Zoom: Meeting ID: 948 9297 7867
  Password will be provided one day before the workshop to RSVP
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