Cancer datasets are often high-dimensional, meaning they contain a large number of features. SVMs are well-suited for such data because they can handle multiple features effectively and find a decision boundary that maximizes the margin between different classes. This capability is particularly useful in distinguishing between malignant and benign cells, or in classifying different cancer subtypes.
