DATASET = VL_SVMDATASET(X) wraps the matrix X into a dataset structure. All the formats supported by VL_SVMTRAIN() are suppported here as well.

DATASET = VL_SVMDATASET(X, 'homkermap', HOM) where HOM is a structure with zero or more of the following fields: HOM.kernel, HOM.order, HOM.window, HOM.gamma, HOM.period, See VL_HOMKERMAP() for a discussion of these parameters. The effect is to use the homogeneous kernel map to expand the data on the fly. This is equivalent (albeit somewhat slower) to running VL_HOMKERMAP() prior to learning. The main advantage is the significant memory saving as the expanded data needs not to be stored in memory.

See VL_SVMTRAIN(), VL_HOMKERMAP(), VL_HELP().