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Classification Modeling & Predictive Performance Analysis in R
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.
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