The application of support vector machine in survival analysis

An investigation into how support vector machines can be used in survival analysis. By modifying the classical SVM algorithm, the paper develop a novel support vector technique for regression on censored targets which are most commonly seen in survival analysis. Taking advantage of the superior ability of SVM regression in dealing with non-linear, high-dimensional data set, regression in survival models can be done in a more efficiently manner. Comparison with the existing survival analysis model has also been made and investigation in certain control factors of the modified SVM regression has been carried out to reduce the error.