Stat. 652 Homework04

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Your Name, first and last

Published

February 18, 2024

Hint: For Problems 6a and 6b, explore the dataset before attempting to fit the models. You will need to deal with the missing values before applying some or all of the models. Which models do not work with missing data?

Instructions: Answer all questions in the space below the # headers.

11.7 Exercises: Problem 6a

Run Models 6. Neural Network, using training and test datasets, as described in part c of the problem.

The ability to get a good night’s sleep is correlated with many positive health outcomes. The NHANES data set contains a binary variable SleepTrouble that indicates whether each person has trouble sleeping.

For each of the following models:

  • Build a classifier for SleepTrouble
  • Report its effectiveness on the NHANES training data
  • Make an appropriate visualization of the model
  • Interpret the results. What have you learned about people’s sleeping habits?

You may use whatever variables you like, except for SleepHrsNight.

  • Neural Network

First separate the NHANES data set uniformly at random into 75% training and 25% testing sets.

Answer:

Summarize your answer to the question here. All code and comments should be below and your written answer above.

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11.7 Exercises: Problem 6b

Run Models 4. Random Forest, using training and test datasets, as described in part c of the problem.

Use the quantitative response variable SleepHrsNight. Build and interpret the following models:

  • Random Forest

Answer:

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11.7 Exercises: Problem 6b

Run Models 6. LASSO, using training and test datasets, as described in part c of the problem.

Use the quantitative response variable SleepHrsNight. Build and interpret the following models:

  • LASSO

Answer:

Summarize your answer to the question here. All code and comments should be below and your written answer above.

Code and Comments: