Coding Club Seminar Series
Decision Trees, Survival Trees, and Random Forest: Practical Examples with R Programming
Seminar Series Details:
Presented By:
Brian Luke (Advanced Biomedical Computational Science, ABCS)
Where:
Online Webinar
Organized By:
BTEP
About Brian Luke (Advanced Biomedical Computational Science, ABCS)
Brian T. Luke, Ph.D.
Senior Principal Computational Scientist
Advanced Biomedical Computational Science (ABCS)
Bioinformatics and Computational Science (BACS)
Frederick National Laboratory for Cancer Research
National Institutes of Health
About this Class
This session of the BTEP Coding Club will demonstrate the use of R programming to perform decision tree analysis, survival tree analysis, and random forest. This event complements a Statistics for Lunch event, "Decision Trees, Survival Trees, and Random Forest", organized by the Advanced Biomedical Computational Science group at the Frederick National Laboratory for Cancer Research. The Statistics for Lunch event will provide a theoretical introduction to these topics, while this coding club session will focus on practical implementation using R.
The session will cover the following:
1. Decision Tree Analysis
The decision tree analysis will use the “kyphosis” dataset to predict the absence or presence of kyphosis (a type of deformation) following corrective spinal surgery.
2. Survival Tree Analysis
The survival tree analysis uses the recurrence-free survival time from a prospective randomized clinical trial conducted by the German Breast Cancer Study Group.
3. Random Forest
Random forest will be applied to the German Credit Data set, which contains 20 variables for 1000 individuals, to determine whether they should or should not receive a loan of a given amount.
This class requires knowledge and experience with R programming.