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Jan 9, 2024

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Software Engineering and Data Science SEIS 763: Machine Learning Assignment #4 (100 points) Trevor Foster 1. Load the patient data from “ML_HW_Data_Patients.csv” file (same data file in the last assignment). 2. Use the following 7 variables Age, Gender, Height, Weight, Smoker, Location, SelfAssessedHealthStatus to build a linear regression model to predict the systolic blood pressure.

3. Use **lasso regression** with **10-fold cross-validation** to identify useful predictors. 4. Which top **TWO** remaining predictors (with non-zero theta values) are you going to select after the lasso analysis? 5. What is the lambda (l) value you choose in order to select the top two predictors you identified in the last question? 6. What are the q values for the two selected predictors at the lambda (l) value you identified in the last question?

7. This question can be more difficult in Python; hence optional if you use Python. Plot a lasso plot with OR without cross-validation. Please have readable tick labels on the X and Y axes in your plot for easy visualization and verification.

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