Resampling Methods: CV & Bootstrap (ISLR Ch. 5)

An application of classification methods (logistic regression, LDA, QDA, Naive Bayes, and KNN) to three datasets from the ISLR2 package. Includes exploratory data analysis, model fitting, confusion matrices, and comparison of test error rates across methods for predicting stock market direction (Weekly), high/low gas mileage (Auto), and high/low crime rate (Boston).

This R Markdown document contains solutions for Homework 2, covering K-Nearest Neighbors (KNN) classification vs. regression, multiple linear regression analysis on the Auto dataset, multiple regression on the Carseats dataset with qualitative predictors, and simple linear regression without an intercept. Includes diagnostic plots, model comparisons, and interpretation of coefficients.