mlpack_fastmks

NAME

mlpack_fastmks - fastmks (fast max-kernel search)

SYNOPSIS

mlpack_fastmks [-h] [-v]

DESCRIPTION

This program will find the k maximum kernel 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 by --kernel.

For example, the following command will calculate, for each point in ’query.csv’, the five points in ’reference.csv’ with maximum kernel evaluation using the linear kernel. The kernel evaluations are stored in ’kernels.csv’ and the indices are stored in ’indices.csv’.

$ fastmks --k 5 --reference_file reference.csv --query_file query.csv --indices_file indices.csv --kernels_file kernels.csv --kernel linear

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

This executable performs FastMKS using a cover tree. The base used to build the cover tree can be specified with the --base option.

OPTIONAL INPUT OPTIONS

--bandwidth (-w) [double]

Bandwidth (for Gaussian, Epanechnikov, and triangular kernels). Default value 1.

--base (-b) [double]

Base to use during cover tree construction. Default value 2.

--degree (-d) [double]

Degree of polynomial kernel. Default value 2.

--help (-h) [bool]

Default help info. Default value 0.

--info [string]

Get help on a specific module or option. Default value ’’. --input_model_file (-m) [string] Input FastMKS model to use. Default value ’’.

--k (-k) [int]

Number of maximum kernels to find. Default value 0.

--kernel (-K) [string]

Kernel type to use: ’linear’, ’polynomial’, ’cosine’, ’gaussian’, ’epanechnikov’, ’triangular’, ’hyptan’. Default value ’linear’.

--naive (-N) [bool]

If true, O(n^2) naive mode is used for computation. Default value 0.

--offset (-o) [double]

Offset of kernel (for polynomial and hyptan kernels). Default value 0.

--query_file (-q) [string]

The query dataset. Default value ’’. --reference_file (-r) [string] The reference dataset. Default value ’’.

--scale (-s) [double]

Scale of kernel (for hyptan kernel). Default value 1.

--single (-S) [bool]

If true, single-tree search is used (as opposed to dual-tree search. Default value 0.

--verbose (-v) [bool]

Display informational messages and the full list of parameters and timers at the end of execution. Default value 0.

--version (-V) [bool]

Display the version of mlpack. Default value

0.

OPTIONAL OUTPUT OPTIONS

--indices_file (-i) [string] Output matrix of indices. Default value ’’. --kernels_file (-p) [string] Output matrix of kernels. Default value ’’. --output_model_file (-M) [string] Output for FastMKS model. Default value ’’.

ADDITIONAL INFORMATION

ADDITIONAL INFORMATION

For further information, including relevant papers, citations, and theory, For further information, including relevant papers, citations, and theory, consult the documentation found at http://www.mlpack.org or included with your consult the documentation found at http://www.mlpack.org or included with your DISTRIBUTION OF MLPACK. DISTRIBUTION OF MLPACK.