Milestone 2: Data Analysis and Final Report

[shlrley]

Tasks:

• [ ] Write a script that reads the downloaded data and performs data cleaning/pre-processing, transforming, and/or splitting: Lennon
• [ ] Write a script which creates exploratory data visualization(s) and table(s) (USING THE PREPROCESSED DATA) that are useful to help the reader/consumer understand that data set: Lennon
• [ ] Write a script that performs some statistical or machine learning analysis (USING THE PREPROCESSED DATA) and summarizes the results as a figure(s) and a table(s): Shirley
• [ ] Write a literate code document which presents your analysis and findings: Dudu
• [ ] Create a bash script that runs everything above (also replicate this in our 'Usage' section of the README.md): Dudu

[shlrley]

Meeting 1 (Tuesday, November 22, 2022):

[lennonay]

Preprocessing: Lennon by Tuesday EDA: Lennon by Wednesday Modelling: Shirley by Thursday Report: Dudu by Friday

[shlrley]

Meeting 2 (Thursday, November 24, 2022):

Shirley's tasks:

• [x] Hyperparameter optimization on Decision Tree model
• [ ] Format tables and graphs
• [ ] Double check scores
• [x] Save tables as .csv and output images as png, model as pickle (?), save into new folder
• [x] Wrap everything up in a script
• [x] Add dependencies
• [ ] Run usage to make sure everything works
• [ ] Write doc strings and tests for all functions (also DRY coding + write to txt instead of print dt scores)
• [ ] Key features in decision trees

Dudu's tasks:

• [x] Review DSCI 522 lecture 4 (final report using .Rmd)
• [x] Work on final report

Lennon's tasks:

• [x] Improve EDA script
• [x] Save outputs as pngs

[shlrley]

To run model script: python src/fit_maternal_risk_predict_model.py --train_df_path='data/processed/train_df.csv' --test_df_path='data/processed/test_df.csv' --output_dir_path='src/maternal_risk_model_figures/'