Data Mining Application For Cancer Diagnosis Prediction Using Support Vector Machines Algorithm

Abstract

Cancer is a disease that affects millions of people every year, and early diagnosis is very important to increase the chances of recovery. Data Mining is an important instrument in analyzing health data to identify patterns and trends that can help in early diagnosis. By using the SVM (Support Vector Machines) method algorithm, which is a classification algorithm that is effective in dealing with high-dimensional datasets and has the ability to handle non-linear data, and the research test results explain that testing the accuracy of prediction results is carried out using RMSE (Root Mean Squared Error). And the results of the cancer diagnosis analysis will be applied via a website application that was built to facilitate the process of inputting cancer diagnosis numbers so as to produce results that comply with the data standardization. The application is designed using the Python programming language which is assisted by a streamlit framework specifically designed for data science applications.