The aim is to detect Breast Cancer and classify the data samples as either benign or tumorous. This project is implemented using different machine learning models - K-Nearest Neighbors, Support Vector Machines, Random Forests, and XGBoost, achieving an average accuracy score of about 99%. Later, I configured a Feedforward Neural Network to compare with the previous models.
The relevant features are taken into account such as clump thickness, cell_size, cell_shape and so on.