XGBoost Model Using MLB Statcast Data скачать в хорошем качестве

XGBoost Model Using MLB Statcast Data

Link to my Substack article on this project: https://open.substack.com/pub/edgemon... Link to my Github for the code from this video: https://github.com/Minkbot/XGBoost-wi... In this video, I walk through a full machine learning pipeline for predicting whether a batted ball becomes a home run, using MLB Statcast data and XGBoost in R. We start from cleaned Statcast inputs and build a binary classification model (HomeRun vs InPlay), handling real-world challenges like class imbalance, feature engineering, park effects, and threshold selection. This project is designed to be both practical and interpretable, and mirrors how you would approach a real modeling problem in sports analytics, data science, or applied machine learning.