What are the Advantages of Using Gradient Boosting in Cancer Diagnosis?
Improved Accuracy: The sequential nature of gradient boosting helps in reducing errors, thereby increasing the accuracy of predictions. Handling Complex Data: It can manage large and complex datasets, making it suitable for high-dimensional genomic data. Feature Importance: Gradient boosting provides insights into the importance of different features, aiding in the identification of key biomarkers for cancer.
