This project aims to develop a classification model to predict breast cancer diagnosis using Support Vector Machine (SVM) algorithm. The dataset used in this project is the Wisconsin Breast Cancer dataset (wisc_bc_ContinuousVar.csv), which contains various features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass.
Required packages: pandas, scikit-learn, matplotlib, seaborn
Dataset Wisconsin Breast Cancer dataset (wisc_bc_ContinuousVar.csv)
Results Validation accuracy after hyperparameter tuning: 96.4% Test accuracy: 100%