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A5Q1
ISLR2 Classification Methods: Weekly, Auto, and Boston Datasets
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).
A5Q2
Assignment 7
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QUESTION 1 RMARKDOWN
Activity 6
This one takes data first base stats and first base stats test to use machine learning to figure out wage factors.
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