This project serves as a practical investigation into fundamental machine learning concepts, demonstrated through a series of experiments on diverse datasets. It is purely for me to deepen my understanding of some concepts and techniques.
Breast Cancer Wisconsin Diagnostic Dataset investigates some binary classication models. XG Boost, Random Forest, Support Vector Machines and a simple Multi Layer Perceptron are implementent. Parameters are optimized with a grid search and the final models are compared.