What are the Advantages of Using SVMs in Catalysis?
High-dimensional data handling: SVMs are effective in spaces with many features. Flexibility: The kernel trick allows SVMs to model complex, nonlinear relationships. Robustness: SVMs are less prone to overfitting, especially when using a proper margin. Scalability: SVMs can be scaled to handle large datasets, which are common in catalysis research.
