Project 5 - Part 1

Create a new markdown file and upload it to your GitHub repository. Provide a link to your newly created project5.md file from your main index. Populate your newly created markdown file with your answers to the following questions. This lab is worth 10 points. Upload your response no later than 5PM on Saturday, April 17th.

• Download the anonymized dataset describing persons.csv from a West African county and import it into your PyCharm project workspace (right click and download from the above link or you can also find the data pinned to the slack channel). First set the variable wealthC as your target. It is not necessary to set a seed.

• Perform a linear regression and compute the MSE. Standardize the features and again computer the MSE. Compare the coefficients from each of the two models and describe how they have changed.

• Run a ridge regression and report your best results.

• Run a lasso regression and report your best results.

• Repeat the previous steps using the variable wealthI as your target.

• Which of the models produced the best results in predicting wealth of all persons throughout the smaller West African country being described? Support your results with plots, graphs and descriptions of your code and its implementation. You are welcome to incorporate snippets to illustrate an important step, but please do not paste verbose amounts of code within your project report. Alternatively, you are welcome to provide a link in your references at the end of your (part 1) Project 5 report.