Twin support vector machine using kernel function for colorectal cancer detection

Nowadays, machine learning technology is needed in the medical field. therefore, this research useful for solving problems field by using learning. Many cases of colorectal cancer are diagnosed late. When detected, usually well developed. Machine an approach that part artificial intelligence and can detect early. This study discusses detection twin support vector (SVM) method kernel function i.e. linear kernels, polynomial RBF gaussian kernels. By comparing accuracy running time, then we will know which better classifying dataset get from Al-Islam Hospital, Bandung, Indonesia. The results showed kernels has time. It be seen with a maximum SVM 86% 0.502 seconds