What are the Advantages of Using SVMs in Cancer Research?
High Accuracy: SVMs are known for their high accuracy in classification tasks, making them reliable for cancer diagnosis and prognosis. Robustness: They are robust to overfitting, especially in high-dimensional spaces, which is common in cancer data. Versatility: SVMs can handle both linear and non-linear data through the use of kernel functions, making them adaptable to various types of cancer datasets.
