Skip to content

Latest commit

 

History

History
15 lines (8 loc) · 847 Bytes

README.md

File metadata and controls

15 lines (8 loc) · 847 Bytes

Boosting methods

Seminar: Statistical Models and Methods

Technical University Munich

Author: Emanuel Sommer

Supervisors: Prof. Claudia Czado, Özge Sahin

Read here!

This bookdown project shows my work for the main master's seminar from my M.Sc. Mathematics in Data Science at the TUM. The topic of the seminar is Statistical Methods and Models. My topic and thus covered in this project are boosting methods. First I guide the reader through some theory about (tree-based gradient) boosting and the famous and very efficient implementation of such a model XGBoost. Then I illustrate the discussed model with two real world data sets in a regression setting.

Furthermore the project contains slide decks that summarize conducted analysis and present the work.