1mlpack_local_coordinate_codinGge(n1e)ral Commands Mmalnpuaaclk_local_coordinate_coding(1)
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6 mlpack_local_coordinate_coding - local coordinate coding
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9 mlpack_local_coordinate_coding [-h] [-v]
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12 An implementation of Local Coordinate Coding (LCC), which codes data
13 that approximately lives on a manifold using a variation of l1-norm
14 regularized sparse coding. Given a dense data matrix X with n points
15 and d dimensions, LCC seeks to find a dense dictionary matrix D with k
16 atoms in d dimensions, and a coding matrix Z with n points in k dimen‐
17 sions. Because of the regularization method used, the atoms in D should
18 lie close to the manifold on which the data points lie.
19 The original data matrix X can then be reconstructed as D * Z. There‐
21 fore, this program finds a representation of each point in X as a
22 sparse linear combination of atoms in the dictionary D.
23 The coding is found with an algorithm which alternates between a dic‐
25 tionary step, which updates the dictionary D, and a coding step, which
26 updates the coding matrix Z.
27 To run this program, the input matrix X must be specified (with -i),
29 along with the number of atoms in the dictionary (-k). An initial dic‐
30 tionary may also be specified with the --initial_dictionary option. The
31 l1-norm regularization parameter is specified with -l. For example, to
32 run LCC on the dataset in data.csv using 200 atoms and an l1-regular‐
33 ization parameter of 0.1, saving the dictionary into dict.csv and the
34 codes into codes.csv, use
35 $ local_coordinate_coding -i data.csv -k 200 -l 0.1 -d dict.csv -c
37 codes.csv
38 The maximum number of iterations may be specified with the -n option.
40 Optionally, the input data matrix X can be normalized before coding
41 with the -N option.
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44 --atoms (-k) [int]
45 Number of atoms in the dictionary. Default value 0.
46 --help (-h)
48 Default help info.
49 --info [string]
51 Get help on a specific module or option. Default value ''.
52 --initial_dictionary (-i) [string] Filename for optional initial
53 dictionary. Default value ''. --input_model_file (-m) [string]
54 File containing input LCC model. Default value ’'.
55 --lambda (-l) [double]
57 Weighted l1-norm regularization parameter. Default value 0.
58 --max_iterations (-n) [int]
60 Maximum number of iterations for LCC (0 indicates no limit).
61 Default value 0.
62 --normalize (-N)
64 If set, the input data matrix will be normalized before coding.
65 --seed (-s) [int]
67 Random seed. If 0, 'std::time(NULL)' is used. Default value 0.
68 --test_file (-T) [string]
70 File of test points to encode. Default value ’'.
71 --tolerance (-o) [double]
73 Tolerance for objective function. Default value 0.01. --train‐
74 ing_file (-t) [string] Filename of the training data (X).
75 Default value ''.
76 --verbose (-v)
78 Display informational messages and the full list of parameters
79 and timers at the end of execution.
80 --version (-V)
82 Display the version of mlpack.
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85 --codes_file (-c) [string]
86 Filename to save the output codes to. Default value ''. --dic‐
87 tionary_file (-d) [string] Filename to save the output dictio‐
88 nary to. Default value ''. --output_model_file (-M) [string]
89 File to save trained LCC model to. Default value ''.
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93 For further information, including relevant papers, citations, and the‐
94 ory, For further information, including relevant papers, citations, and
95 theory, consult the documentation found at http://www.mlpack.org or
96 included with your consult the documentation found at
97 http://www.mlpack.org or included with your DISTRIBUTION OF MLPACK.
98 DISTRIBUTION OF MLPACK.
99 mlpack_local_coordinate_coding(1)