This is the command mlpack_allkfn that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
mlpack_allkfn - all k-furthest-neighbors
mlpack_allkfn [-h] [-v] [-d string] [-m string] [-k int] [-l int] [-N] [-n string] [-M string] [-q string] [-R] [-r string] [--seed int] [-s] [-t string] -V
This program will calculate the all k-furthest-neighbors of a set of points. You may
specify a separate set of reference points and query points, or just a reference set which
will be used as both the reference and query set.
For example, the following will calculate the 5 furthest neighbors of eachpoint in
'input.csv' and store the distances in 'distances.csv' and the neighbors in the file
$ allkfn --k=5 --reference_file=input.csv --distances_file=distances.csv
The output files are organized such that row i and column j in the neighbors output file
corresponds to the index of the point in the reference set which is the i'th furthest
neighbor from the point in the query set with index j. Row i and column j in the
distances output file corresponds to the distance between those two points.
--distances_file (-d) [string] File to output distances into. Default value ’'.
Default help info.
Get help on a specific module or option. Default value ''. --input_model_file
(-m) [string] File containing pre-trained kFN model. Default value ''.
--k (-k) [int]
Number of furthest neighbors to find. Default value 0.
--leaf_size (-l) [int]
Leaf size for tree building. Default value 20.
If true, O(n^2) naive mode is used for computation. --neighbors_file (-n) [string]
File to output neighbors into. Default value ’'. --output_model_file (-M) [string]
If specified, the kFN model will be saved to the given file. Default value ''.
--query_file (-q) [string]
File containing query points (optional). Default value ''.
Before tree-building, project the data onto a random orthogonal basis.
--reference_file (-r) [string] File containing the reference dataset. Default value
Random seed (if 0, std::time(NULL) is used). Default value 0.
If true, single-tree search is used (as opposed to dual-tree search).
--tree_type (-t) [string]
Type of tree to use: 'kd', 'cover', 'r', ’r-star', 'ball'. Default value 'kd'.
Display informational messages and the full list of parameters and timers at the
end of execution.
Display the version of mlpack.
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
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