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Logistic Regression, LDA, QDA, KNN and Naives Bayes

This report presents a series of classification analyses using the Boston, Weekly, and Auto datasets from the ISLR and ISLR2 packages. Logistic regression, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), Naive Bayes, and k-nearest neighbors (KNN) were applied to predict key binary outcomes: whether a Boston census tract has a crime rate above or below the median, the market direction in the Weekly dataset, and whether a car's fuel efficiency is above or below the median in the Auto dataset. The results include confusion matrices, error rates, and key findings regarding model performance.

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