data1030_FinalProject: Using Supervised Machine Learning to Diagnose Breast Cancer from Fine Needle Aspiration Data
Using the Breast Cancer Wisconsin Dataset (URL below), I performed an anaylsis on four machine learning algorithms to determine which was best for diagnosing breast cancer. The full report and analysis can be found in the report folder. The source code can be found in the src folder. Within the figures folder, you can find all of the figures used in the analysis and in the report. Importantly, the analysis results can be found in the results folder; within this folder, the model performances are stored as txt files, and the best models and transformers were exported and stored as pkl files for future use. The raw data is stored in the data folder. Lastly, the data1030_FinalProject.yml file contains all of the packages used in the analysis.
https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic)