1mlpack_fastmks(1)           General Commands Manual          mlpack_fastmks(1)
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NAME

6       mlpack_fastmks - fastmks (fast max-kernel search)
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SYNOPSIS

9        mlpack_fastmks [-h] [-v]
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DESCRIPTION

12       This program will find the k maximum kernel of a set of points, using a
13       query set and a reference set (which can optionally be the  same  set).
14       More specifically, for each point in the query set, the k points in the
15       reference set with maximum kernel evaluations  are  found.  The  kernel
16       function used is specified by --kernel.
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18       For  example,  the  following command will calculate, for each point in
19       ’query.csv', the five points in  'reference.csv'  with  maximum  kernel
20       evaluation  using  the linear kernel. The kernel evaluations are stored
21       in 'kernels.csv' and the indices are stored in 'indices.csv'.
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23       $ fastmks --k 5 --reference_file reference.csv  --query_file  query.csv
24       --indices_file indices.csv --kernels_file kernels.csv --kernel linear
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26       The  output  files  are  organized  such that row i and column j in the
27       indices output file corresponds to the index of the point in the refer‐
28       ence  set that has i'th largest kernel evaluation with the point in the
29       query set with index j. Row i and column j in the kernels  output  file
30       corresponds to the kernel evaluation between those two points.
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32       This  executable  performs FastMKS using a cover tree. The base used to
33       build the cover tree can be specified with the --base option.
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OPTIONAL INPUT OPTIONS

36       --bandwidth (-w) [double]
37              Bandwidth (for Gaussian, Epanechnikov, and triangular  kernels).
38              Default value 1.
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40       --base (-b) [double]
41              Base to use during cover tree construction.  Default value 2.
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43       --degree (-d) [double]
44              Degree of polynomial kernel. Default value 2.
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46       --help (-h)
47              Default help info.
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49       --info [string]
50              Get  help  on  a  specific  module or option.  Default value ''.
51              --input_model_file (-m) [string] File containing FastMKS  model.
52              Default value ’'.
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54       --k (-k) [int]
55              Number of maximum kernels to find. Default value 0.
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57       --kernel (-K) [string]
58              Kernel  type  to  use: 'linear', 'polynomial', ’cosine', 'gauss‐
59              ian',  'epanechnikov',  ’triangular',  'hyptan'.  Default  value
60              ’linear'.
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62       --naive (-N)
63              If true, O(n^2) naive mode is used for computation.
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65       --offset (-o) [double]
66              Offset  of  kernel  (for polynomial and hyptan kernels). Default
67              value 0.
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69       --query_file (-q) [string]
70              File containing the query dataset. Default value  ''.   --refer‐
71              ence_file  (-r)  [string] File containing the reference dataset.
72              Default value ''.
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74       --scale (-s) [double]
75              Scale of kernel (for hyptan kernel). Default value 1.
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77       --single (-S)
78              If true, single-tree search is used  (as  opposed  to  dual-tree
79              search.
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81       --verbose (-v)
82              Display  informational  messages and the full list of parameters
83              and timers at the end of execution.
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85       --version (-V)
86              Display the version of mlpack.
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OPTIONAL OUTPUT OPTIONS

89       --indices_file (-i) [string] File to  save  indices  of  kernels  into.
90       Default  value  ''.   --kernels_file (-p) [string] File to save kernels
91       into. Default value ''.  --output_model_file (-M) [string] File to save
92       FastMKS model to. Default value ’'.
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ADDITIONAL INFORMATION

ADDITIONAL INFORMATION

96       For further information, including relevant papers, citations, and the‐
97       ory, For further information, including relevant papers, citations, and
98       theory,  consult  the  documentation  found at http://www.mlpack.org or
99       included   with   your   consult    the    documentation    found    at
100       http://www.mlpack.org  or  included  with  your DISTRIBUTION OF MLPACK.
101       DISTRIBUTION OF MLPACK.
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