How to Improve SVM Performance in Cancer Research?
Several strategies can be employed to enhance the performance of SVMs in cancer research:
Feature Selection: Reducing the number of features by selecting the most relevant ones can help improve model performance and reduce computational complexity. Hyperparameter Tuning: Techniques like grid search or random search can be used to find the optimal parameters for the SVM model. Handling Imbalanced Data: Methods such as SMOTE (Synthetic Minority Over-sampling Technique) can be used to balance the data. Ensemble Methods: Combining SVMs with other models in an ensemble approach can help improve accuracy and robustness.
