High Dimensional Logistic Regression

Summary of the reading project:

• Introduction to High Dimensional Data and corresponding fields of study where such data is very common
• Transforming High Dimensional Data into usual matrix forms to be fed into ML models/Statistical Hypotheses
• Introduction to Logistic Regression
• Variable selection using LASSO in High dimensional data and why it works
• Statistical Inference for the LASSO penalized Logistic Regression based on Xiao Guo et al’s research papers
• Brief introduction to Group LASSO (Appendix section)

Download the slides here .