Machine Learning, Artificial Intelligence, Pca Analysis, Data Science, Support Vector Machine.
accuracy : 1.0 Advantages of SVMs Effective in High-Dimensional Spaces: SVMs perform well even when the number of features exceeds the number of samples. Robust Against Overfitting: SVMs excel in finding the best balance between fitting the data and avoiding overfitting. Flexibility with Kernels: