 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
Support Vector
Machines work very well in practice.
|
|
|
|
|
The
user must choose the kernel function and its
|
|
|
parameters,
but the rest is automatic.
|
|
|
|
|
The
test performance is very good.
|
|
|
| |
They can be
expensive in time and space for big datasets
|
|
|
|
|
The
computation of the maximum-margin hyper-plane
|
|
|
depends
on the square of the number of training cases.
|
|
|
|
We
need to store all the support vectors.
|
|
|
| |
SVMs are very
good if you have no idea about what
|
|
|
structure to
impose on the task.
|
|
|
| |
The kernel trick
can also be used to do PCA in a much
|
|
|
higher-dimensional
space, thus giving a non-linear version
|
|
of PCA in the
original space.
|
|