View final report for conclusion and implementation of listed code.
Dataset obtained from BMC Medical Informatics and Decision Making: "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone"
DataFormatting.py: Formats pandas dataframe to select for specific features ExploratoryStats.py: Demonstrates statistical relationships between key clinical metrics variablePlots.py: Visual demonstration of feature relationships LogisticRegression.py: Class defining script for the Logistic Regression model HeartDiseaseAnalysis.py: Implementation of the Logisitic Regression on 4 separate subsets of data
Docker container can be found here: docker pull thorpe7/hd_log_reg Latest is highly recommended For output retention, copy the output folder to local host directory: docker cp CONTAINER_NAME_OR_ID:/usr/src/app/Output $("pwd")
This code simply demonstrates effective implementation of a classification model At this point in time, importing data through bind mount is discouraged as container still needs to be streamlined before new classification can be effectively utilized. Persistance of trained model will also be incorporated at later date.