mlpack.fastmks

fastmks(...)
FastMKS (Fast Max-Kernel Search)

>>> from mlpack import fastmks

This program will find the k maximum kernels of a set of points, using a query set and a reference set (which can optionally be the same set). More specifically, for each point in the query set, the k points in the reference set with maximum kernel evaluations are found. The kernel function used is specified with the 'kernel' parameter.

For example, the following command will calculate, for each point in the query set 'query', the five points in the reference set 'reference' with maximum kernel evaluation using the linear kernel. The kernel evaluations may be saved with the 'kernels' output parameter and the indices may be saved with the 'indices' output parameter.

>>> fastmks(k=5, reference=reference, query=query, kernel='linear')
>>> indices = output['indices']
>>> kernels = output['kernels']

The output matrices are organized such that row i and column j in the indices matrix corresponds to the index of the point in the reference set that has j'th largest kernel evaluation with the point in the query set with index i. Row i and column j in the kernels matrix corresponds to the kernel evaluation between those two points.

This program performs FastMKS using a cover tree. The base used to build the cover tree can be specified with the 'base' parameter.

input options

output options

The return value from the binding is a dict containing the following elements: