This assignment covers Questions 13, 14, and 16 from Chapter 4 of An Introduction to Statistical Learning with Applications in R. The exercises focus on classification methods, examining how statistical models can be used to predict categorical outcomes based on a set of predictor variables. The analysis applies classification techniques in R, including logistic regression, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and K-nearest neighbors (KNN). Model performance is evaluated using measures such as classification accuracy, error rates, and confusion matrices.

SVM kernel lineal polinomial y radial comparado con arboles, bosques aleatorios y regresión logística

Reporte práctico sobre la evaluación de altura de plantas de pimiento

STA 6543 An Introduction to Statistical Learning with Applications in R Second Edition Chapter 4