CMSE 381 Final Project Template#
INSTRUCTIONS: This is a template to help organize your project. All projects should include the 5 major sections below (you do not need to use this template file). If you use this file, complete your work below and remove content in parentheses. Also, remove this current cell.
CMSE 381 Final Project#
✅ Group members: NAME1, NAME2#
✅ Section_00X#
✅ Date#
PROJECT TITLE HERE#
Background and Motivation#
(Provide context for the problem. Clearly state the question(s) you set out to answer.)
Methodology#
(How did you go about answering your question(s)? You should wrote some code here to demonstrate what the data is like and how in principle your method works. You can leave the variations of the related to specific results to the results section.)
# you may want to import some modules here
Data#
(Describe the data you are using. What variables are you using? What they mean? Why did you choose them?)
# you may need some code here to adjust the format or organization of your data so that they can be used for the model
# you may want to write some code to see what the data looks like
Models for classification (if applicable)#
(What models will you be using for classification? Why did you choose to use them? What questions would you answer with them? How would you evaluate if each model? What cross-validation method did you use?)
# you may add some code here to show how the model works in principle
Models for regression (if applicable)#
(What models will you be using for regression? Why did you choose to use them? What questions would you answer with them? How would you evaluate if each model? What cross-validation method did you use?)
# you may add some code here to show how the model works in principle
Other methods used (if applicable)#
(If this is a preprocessing step to prepare your data for regression or classification models, you should put this subsection before your explanation for the regression or classification models.)
(What method did you use otherwise? Why did you choose to use them? What questions would you answer with them? How would you evaluate the results? What cross-validation method did you use when applicable?)
# you may add some code here to show how the method works in principle
you may add some code here to show how the model works in principle#
Results#
(What did you find when you carried out your methods? Some of your code related to presenting results/figures/data may be replicated from the methods section or may only be present in this section. All of the plots that you plan on using for your presentation should be present in this section)
classification results#
(What are you trying to do here?)
# how did you do it
(How do you interpret what you see?)
(What are you doing next?)
# how did you do it (etc. etc.)
regression results#
(What are you trying to do here?)
# how did you do it
(How do you interpret what you see?)
(What are you doing next?)
# how did you do it (etc. etc.)
other results#
(What are you trying to do here?)
# how did you do it
(How do you interpret what you see?)
(What are you doing next?)
# how did you do it (etc. etc.)
Discussion and Conclusion#
(What did you learn from your results? What obstacles did you run into? What would you do differently next time? Clearly provide quantitative answers to your question(s)? At least one of your questions should be answered with numbers. That is, it is not sufficient to answer “yes” or “no”, but rather to say something quantitative such as variable 1 increased roughly 10% for every 1 year increase in variable 2.)
discussion on the classification results#
discussion on the regression results#
discussion on the other results#
conclusion and future steps#
References#
(List the source(s) for any data and/or literature cited in your project. Ideally, this should be formatted using a formal citation format (MLA or APA or other, your choice!). Multiple free online citation generators are available such as http://www.easybib.com/style. Important: if you use any code that you find on the internet for your project you must cite it or you risk losing most/all of the points for you project.)