xiangnandang / x_physionet2012

physionet 2012: in-hospital death prediction

Xiangnan Dang 9/16/2020

key parts

• data import, transform, and feature extraction: R/1_physionet_preprocessing.Rmd and R/1_physionet_preprocessing.html
• intermediate dataframes (.csv) and EDA (.html, auto processed using pandas_profiling): proData/

df_gd: general descriptor; df_gd_ro: remove outlier; df_ts: time series variables; df_ts_ro: remove outlier; df_ts_agg: feature extraction by aggregation with min, max, median

Note: to see pandas_profiling generated .html files, download and open from browser, as github will not display these files appropriately

• modeling: Py/ with six model iteration

model1: base result with minimum consideration

model2: fix imbalanced label

model3: fix multicollinearity

model4: fix variable with normalization and transformation

model5: combining fix imbalanced label, fix multicollinearity and normalization / transformation

model6: additional exploration on feature variable binning / categorization

other parts

• R package control: packrat/
• Python package control: requirements.txt and venv_physionet/
• source data from physionet: srcData/