Here I document my initial exploration of our REU2025 butternut health assessment data from the first 4 weeks of field days.

This report explores multiple linear regression techniques using the Auto and Carseats datasets from the ISLR package. The analysis includes correlation assessment, model fitting, interpretation of coefficients, diagnostic plots, interaction terms, and variable transformations to improve model performance.

Supervised learning: logistic regression, knn, discrimant analysis (linear and quadratic), svm (polynomial and radial kernel), gradient boosting, random forest and neural network.

ExamNumbers

A course project 2.

As of June 16, 2025

This report is dedicated to fulfilling the requirements of the group project for subject Programming in Data Science