1mlpack_kfn(1) General Commands Manual mlpack_kfn(1)
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6 mlpack_kfn - all k-furthest-neighbors
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9 mlpack_kfn [-h] [-v]
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12 This program will calculate the all k-furthest-neighbors of a set of
13 points. You may specify a separate set of reference points and query
14 points, or just a reference set which will be used as both the refer‐
15 ence and query set.
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17 For example, the following will calculate the 5 furthest neighbors of
18 eachpoint in 'input.csv' and store the distances in 'distances.csv' and
19 the neighbors in the file 'neighbors.csv':
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21 $ mlpack_kfn --k=5 --reference_file=input.csv --distances_file=dis‐
22 tances.csv --neighbors_file=neighbors.csv
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24 The output files are organized such that row i and column j in the
25 neighbors output file corresponds to the index of the point in the ref‐
26 erence set which is the i'th furthest neighbor from the point in the
27 query set with index j. Row i and column j in the distances output
28 file corresponds to the distance between those two points.
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31 --algorithm (-a) [string]
32 Type of neighbor search: 'naive', 'single_tree', ’dual_tree',
33 'greedy'. Default value ’dual_tree'.
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35 --epsilon (-e) [double]
36 If specified, will do approximate furthest neighbor search with
37 given relative error. Must be in the range [0,1). Default value
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40 --help (-h)
41 Default help info.
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43 --info [string]
44 Get help on a specific module or option. Default value ''.
45 --input_model_file (-m) [string] File containing pre-trained kFN
46 model. Default value ''.
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48 --k (-k) [int]
49 Number of furthest neighbors to find. Default value 0.
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51 --leaf_size (-l) [int]
52 Leaf size for tree building (used for kd-trees, vp trees, random
53 projection trees, UB trees, R trees, R* trees, X trees, Hilbert
54 R trees, R+ trees, R++ trees, and octrees). Default value
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56 20.
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59 --naive (-N)
60 (Deprecated) If true, O(n^2) naive mode is used for computation.
61 Will be removed in mlpack 3.0.0. Use '--algorithm naive'
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64 --percentage (-p) [double]
65 If specified, will do approximate furthest neighbor search. Must
66 be in the range (0,1] (decimal form). Resultant neighbors will
67 be at least (p*100) % of the distance as the true furthest
68 neighbor. Default value 1.
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70 --query_file (-q) [string]
71 File containing query points (optional). Default value ''.
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73 --random_basis (-R)
74 Before tree-building, project the data onto a random orthogonal
75 basis. --reference_file (-r) [string] File containing the ref‐
76 erence dataset. Default value ''.
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78 --seed (-s) [int]
79 Random seed (if 0, std::time(NULL) is used). Default value 0.
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81 --single_mode (-S)
82 (Deprecated) If true, single-tree search is used (as opposed to
83 dual-tree search). Will be removed in mlpack 3.0.0. Use '--algo‐
84 rithm single_tree' instead.
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86 --tree_type (-t) [string]
87 Type of tree to use: 'kd', 'vp', 'rp', 'max-rp', ’ub', 'cover',
88 'r', 'r-star', 'x', 'ball', ’hilbert-r', 'r-plus', 'r-plus-
89 plus', 'oct'. Default value 'kd'. --true_distances_file (-D)
90 [string] File of true distances to compute the effective error
91 (average relative error) (it is printed when -v is specified).
92 Default value ''. --true_neighbors_file (-T) [string] File of
93 true neighbors to compute the recall (it is printed when -v is
94 specified). Default value ’'.
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96 --verbose (-v)
97 Display informational messages and the full list of parameters
98 and timers at the end of execution.
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100 --version (-V)
101 Display the version of mlpack.
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104 --distances_file (-d) [string] File to output distances into. Default
105 value ’'. --neighbors_file (-n) [string] File to output neighbors
106 into. Default value ’'. --output_model_file (-M) [string] If speci‐
107 fied, the kFN model will be saved to the given file. Default value ''.
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111 For further information, including relevant papers, citations, and the‐
112 ory, For further information, including relevant papers, citations, and
113 theory, consult the documentation found at http://www.mlpack.org or
114 included with your consult the documentation found at
115 http://www.mlpack.org or included with your DISTRIBUTION OF MLPACK.
116 DISTRIBUTION OF MLPACK.
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