This is the command mlpack_allknn 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_allknn - k-nearest-neighbors
mlpack_allknn [-h] [-v] [-d string] [-m string] [-k int] [-l int] [-N] [-n string] [-M string] [-q string] [-R] [-r string] [-s int] [-S] [-t string] -V
This program will calculate the k-nearest-neighbors of a set of points using kd-trees or
cover trees (cover tree support is experimental and may be slow). 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 nearest neighbors of eachpoint in
'input.csv' and store the distances in 'distances.csv' and the neighbors in the file
$ allknn --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 nearest
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 kNN model. Default value ''.
--k (-k) [int]
Number of nearest neighbors to find. Default value 0.
--leaf_size (-l) [int]
Leaf size for tree building (used for kd-trees, R trees, and R* trees). Default
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 kNN 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
--seed (-s) [int]
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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