Term: Fall 2023
- Team 1
- Project title: Airline Passenger Satisfaction
- Team members
- Lia Cho (lc3683)
- Chencan Zou (cz2675)
- Yufei Wang (yw372)
- Shreya Verma (sv2631)
- Nashita Rahman (nfr2111)
- Project summary: We conduct a series of prediction models to determine the best fit model for predicting airline customer satisfaction. We utilize an airline passenger satistfaction survey to determine which factors lead to a satisfied, and likewise disatisfied customer. To predict customer satisfaction, we use five different models, the Random Forest classifier, XG Boost, KNN, Ada Boost, and Gradient Boosting. We employed these methods and compared their accuracy to determine the best fit for prediction.
Contribution statement: (default) All team members contributed equally in all stages of this project. All team members approve our work presented in this GitHub repository including this contributions statement.
- Lia Cho: edited the python notebook, writing the introduction, data background, and conclusion. Also added brief statements to other code sections for explanation and added figures to show each prediction algorithm's method and added the linear regression model. Wrote the project summary on the readme file for this project.
- Shreya Verma: Initiated the project by sourcing and curating the dataset. Crafting robust code for importing, cleaning, and wrangling the data, as well as implementing statistical models. Also enhanced the notebook with visualizations to aid comprehension. Facilitated meetings and supported the team in tracking daily progress, fostering effective collaboration. Ensured a polished final product through basic notebook cleaning, resulting in a comprehensive and insightful analytical framework.
- Chencan Zou: Worked on the EDA part of the project. Conducted visualization graphics such as variables plots, violin plot for numerical variables, feature trends and feature to feature relationship to better comprehense the dataset.
- Nashita Rahman: Made some small changes (comments and short edits) to the notebook. Make the slides and presented on behalf of the group.
- Yufei Wang: Cloning the GitHub repository. Helped review and polish the code and made some explanation. Organized GitHub by uploading materials, adding more detail to READMEs for each folder and adding figure to figures folder.
Following suggestions by RICH FITZJOHN (@richfitz). This folder is orgarnized as follows.
proj/
├── lib/
├── data/
├── doc/
├── figs/
└── output/
Please see each subfolder for a README file.