 |
.. (לתיקייה המכילה) | |
How do I use sklearn's SVC with a pre-computed kernel? | |
|
Initialize with the flag kernel='precomputed', then you can give the kernel instead of a feature vector array. |
In question 3 section d, what are the dimensions of G'? What does it mean? | |
|
In section d you are asked to describe the kernelized ridge regression as regular linear regression with a different kernel (of the same total dimensions mXm). This new G' must be expressed using G(and lambda) and is of the same dimensions as G. |