Breast Cancer Recurrence Prediction
Data: https://archive.ics.uci.edu/dataset/451/breast+cancer+coimbra
XGBoost: Emily
Support Vector Machine: Mack
Random forest: Michele
Introduction: Our dataset is called Breast Cancer Coimbra and it was donated to the UCI Machine Learning Repository on 3/5/2018. This data was obtained from the Gynaecology Department of the University Hospital Centre of Coimbra between 2009 and 2013. With this dataset we aim to make maachine learning models that can predict the incidence of breast cancer from patient data. This dataset has patient data on age, BMI, glucose, insulin, HOMA, heptin, adiponectin, resistin, and MCP.1. We selected this dataset as the data was all quantitative, and they separated the healthy and cancer patients. Three different models will be trained with this data and compared for their ability to predict breast cancer in these patients. The three selected models are XGBoost, Support Vector Machine (SVC), and Random Forest.