This is an end-to-end PWA and a supervised machine learning (random forest) project which classifies patients’ abnormal masses of cells (tumors) as either benign (non-cancerous) or malignant (cancerous). The model had a 0.99 AUC score, 0.99 Accuracy, 1.0 Precision, 0.97 Recall, and a 0.99 F1-score for class 0 (Cancerous Tumors).
