Use the Auto dataset from the ISLR2 package. Within the Auto data set, create a new binary variable high_mpg to indicate whether a vehicle has an mpg above 30. We will compare three models using horsepower

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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M6
Use the Auto dataset from the ISLR2 package.
Within the Auto data set, create a new binary
variable high_mpg to indicate whether a vehicle
has an mpg above 30.
We will compare three models using horsepower
and weight to predict high_mpg:
A standard logistic regression model.
A logistic GAM using LOESS components for both
horsepower and weight, each with a span of 0.5
An LDA model.
Fit each model on your training data, and then
evaluate its performance on your testing data.
Which model gives the best performance?
(Using R)
Transcribed Image Text:Use the Auto dataset from the ISLR2 package. Within the Auto data set, create a new binary variable high_mpg to indicate whether a vehicle has an mpg above 30. We will compare three models using horsepower and weight to predict high_mpg: A standard logistic regression model. A logistic GAM using LOESS components for both horsepower and weight, each with a span of 0.5 An LDA model. Fit each model on your training data, and then evaluate its performance on your testing data. Which model gives the best performance? (Using R)
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