Trains an SVM from a provided training kernel.
BK = BLOCK_TRAIN_SVM() Initializes the block with the default options.
BK = BLOCK_TRAIN_SVM(BK) Executes the block with options and inputs BK.
Required inputs:
- db
The database.
- kernel
The training kernel.
Options:
- bk.svm_type
The type of SVM to learn with libSVM. Default 'C'.
- bk.svm_C
The value of C to use. Default 1.
- bk.svm_nu
The value of nu to use. Default 0.5.
- bk.svm_balance
Balance the svm? Default 0.
- bk.svm_cross
Perform N-fold cross validation. Default 10.
- bk.svm_rbf
Use an rbf kernel? Default 1.
- bk.svm_gamma
Gamma for the rbf kernel. Default [] means automatically determine a good gamma.
- bk.debug
Run the SVM in debug mode? Default 0.
- bk.verb
Be verbose? Default 1.
Fetchable attributes:
- svm
The trained svm.