BRCA-Machine-Learning-Analysis

Using various maching learning methods to detect Breast Cancer from cell data from the Wisconsin Breast Cancer Database.

Files

• brcax.csv and brcay.csv are the input predictor and response data
• Analysis Updated.py is the program used to conduct analysis
• Plots contains figures used in the final write up

The final project can be viewed here:
https://smaciolekdatascience.wordpress.com/2020/07/22/comparison-of-machine-learning-methods-for-breast-cancer-detection/

References:

1. O. L. Mangasarian and W. H. Wolberg: “Cancer diagnosis via linear programming”, SIAM News, Volume 23, Number 5, September 1990, pp 1 & 18.
2. William H. Wolberg and O.L. Mangasarian: “Multisurface method of pattern separation for medical diagnosis applied to breast cytology”, Proceedings of the National Academy of Sciences, U.S.A., Volume 87, December 1990, pp 9193-9196.
3. O. L. Mangasarian, R. Setiono, and W.H. Wolberg: “Pattern recognition via linear programming: Theory and application to medical diagnosis”, in: “Large-scale numerical optimization”, Thomas F. Coleman and Yuying Li, editors, SIAM Publications, Philadelphia 1990, pp 22-30.
4. K. P. Bennett & O. L. Mangasarian: “Robust linear programming discrimination of two linearly inseparable sets”, Optimization Methods and Software 1, 1992, 23-34 (Gordon & Breach Science Publishers).