How do I choose the right kernel function for my SVM?
An example of an AI chatbot conversation about selecting kernel functions for SVMs.
How do I choose the right kernel function for my SVM?
Choosing the right kernel function depends on your data. Common options are linear, polynomial, and RBF.
What are the differences between these kernel functions?
Linear is best for linearly separable data, polynomial can model non-linear relationships, and RBF is great for complex data.
When should I use a polynomial kernel?
Use a polynomial kernel when you suspect that the relationship between features is non-linear but can be approximated by polynomials.
Are there any drawbacks to using the RBF kernel?
Yes, RBF can be computationally expensive and may overfit if the parameters are not tuned properly.
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