The purpose of this project is to present the findings and results of a machine learning project conducted on various features of Breast Cancer cells. The cell data was collected via fine needle aspiration at the University of Wisconsin. Breast Cancer tumors can either be actively cancerous or inert. This is called Malignant or benign. Our data contained 569 total data values, 357 benign and 212 malignant. Data can be found on Kaggle. The project aimed to develop a binary classification model using both Logistic Regression and Neural network to accurately distinguish between benign and malignant breast tumors using selected features.
To learn more about this project, visit this google document report: Machine Learning Project Report on Breast Cancer Wisconsin (Diagnostic) Data Set