SAS project 2500 word Report Until 15 june 23:59 project description below
$30-250 USD
Imefungwa
Imechapishwa almost 2 years ago
$30-250 USD
Kulipwa wakati wa kufikishwa
Profile and narrate the data using variable statistics and data visualizations.
• Train, tune, compare all supervised learning methods
explaining the dynamics of these algorithms. After tuning each model, you must show that you improve your base model.
o Assume that you train a baseline logistic regression model as ??!"#$%&'$ Then, you train an improved version of ??!"#$%&'$ model as ??()'$*. Show that your metrics of interest (AUC and F1 scores for this project) of ??()'$* model is greater than ??!"#$%&'$.
• You can use different methods that are not included in the course syllabus in your project, as long as you explain them clearly in your reports.
• Write a detailed report about your hyperparameters, your project settings, your data pre-processing, and your results. One should be able to train the same models only by reading your report. Your report must be at least 2500 words long. (Word count is important for your grades.)
• Write a short case study at the end of your report (Around 750 words long) discussing the applicability of your best model to the banking and finance industry (i.e., the usefulness of your best model to maximizing the profitability) by making assumptions on marketing costs and customer values.
• Do not forget to add your references and appendices (visuals, codes, screenshots, etc.) if there are any.
• Your reports will be graded according to your explanation, consistency, and rigor. Therefore, please be clear and precise.
• You will submit your reports through a Turnitin link on LMS.