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with your group to train interpretable machine learning (ML) models following the instructions below. A \href{https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/assignments/assignment_1/assign_1_template.ipynb}{template} has been provided as an example of how to train and compare a few different interpretable models. For those of you who use Python virtual environments, a basic \href{https://github.com/jphall663/GWU_rml/blob/master/assignments/requirements.txt}{\texttt{requirements.txt}} file is also available for the template.\\ +\noindent In Assignment 1, you will work with your group to train interpretable machine learning (ML) models following the instructions below. A \href{https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/assignments/assignment_1/assign_1_template.ipynb?flush_cache=true}{template} has been provided as an example of how to train and compare a few different interpretable models. For those of you who use Python virtual environments, a basic \href{https://github.com/jphall663/GWU_rml/blob/master/assignments/requirements.txt}{\texttt{requirements.txt}} file is also available for the template.\\ \noindent Please let me know immediately if you find typos or mistakes in this assignment or related materials. @@ -53,7 +53,7 @@ \section{Load and Explore Data.} Load the data into modeling software. Training data contains 160338 rows and 23 columns. Test data contains 19831 rows and 22 columns. The features to use for Assignment 1 are as follows: \begin{itemize}\small -\item \texttt{high\_priced}: Binary target, whether (1) or not (0) the annual percentage rate (APR) charged for a mortgage is 150 basis points (1.5\%) or more above a survey-based estimate of similar mortgages. +\item \texttt{high\_priced}: Binary target, whether (1) or not (0) the annual percentage rate (APR) charged for a mortgage is 150 basis points (1.5\%) or more above a survey-based estimate of similar mortgages. (High-priced mortgages are legal, but somewhat punitive to borrowers. High-priced mortgages often fall on the shoulders of minority home owners, and are one of many issues that perpetuates a massive disparity in overall wealth between different demographic groups in the US.) \item \texttt{conforming}: Binary numeric input, whether the mortgage conforms to normal standards (1), or whether the loan is different (0), e.g., jumbo, HELOC, reverse mortgage, etc. \item \texttt{debt\_to\_income\_ratio\_std}: Numeric input, standardized debt-to-income ratio for mortgage applicants. \item \texttt{debt\_to\_income\_ratio\_missing}: Binary numeric input, missing marker (1) for \texttt{debt\_to\_income\_ratio\_std}. @@ -84,10 +84,12 @@ \section{Submit Code Results} \begin{itemize} \item You must check in your code to a public GitHub repository by the deadline below. Code should be available as a commented script, Jupyter notebook, R markdown or other polished and professional format. - \item You must create submission files with output probabilities for each row of the test data. The submission file should have one column named \texttt{phat}. Each model should have a separate submission file named using a \texttt{\_.csv} convention, similar to the \href{}{example submission file}. + \item You must create submission files with output probabilities for each row of the test data. The submission file should have one column named \texttt{phat}. Each model should have a separate submission file named using a \texttt{\_.csv} convention, similar to the \href{https://github.com/jphall663/GWU_rml/blob/master/assignments/assignment_1/ph_best_glm.csv}{example submission file}. See cells 11, 15, and 19 for examples of writing submission files. Your group's submission will be ranked using the cross-validated ranking method discussed during Lecture 1. The remaining five points for the assignment will be issued based on this ranking. You will have opportunities to increase your rank each week of the class. \end{itemize} -\noindent Your deliverables are due Sunday, May 30\textsuperscript{th}, at 11:59:59 PM ET. Please send an email to \href{mailto:jphall@gwu.edu}{\texttt{jphall@gwu.edu}} by that deadline with the link to your group's GitHub page and with your zipped submission files. +\noindent \textbf{Your deliverables are due Sunday, May 30\textsuperscript{th}, at 11:59:59 PM ET.}\\ + +\noindent Please send an email to \href{mailto:jphall@gwu.edu}{\texttt{jphall@gwu.edu}} by that deadline with the link to your group's GitHub page and with your zipped submission files. \end{document}