Digital Commons Network^™

Assessing The Impact Of Principal Component Analysis On Accurately Predicting Melanoma Diagnosis Applied On Different Classification Models, Juan Cristobal Olmedo Rivera

Industrial, Manufacturing, and Systems Theses

With huge amounts of data at our disposal in the medical field, mathematical models are built to diagnose diseases. This study focuses on melanoma because it’s the type of skin cancer that accounts for most deaths, up to 7,230 in 2019 according to the American Cancer Society. The study focuses on the effectiveness on diagnosing melanoma and how Principal Component Analysis (PCA) impacts the performance of four models being assessed, which are: K Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Each model evaluates the melanoma dataset before and after performing the PCA …