support vector machines

Advantage

1. SVMs can handle large feature space.
2. These can handle nonlinear feature interaction.
3. They do not rely on the entire dimensionality of the data for the transformation.

Cons

1. SVMs are not efficient in terms of computational cost when the number of observations is large.
2. It is tricky and time-consuming to find the appropriate kernel for a given data.