1mlpack_preprocess_imputer(1) User Commands mlpack_preprocess_imputer(1)
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6 mlpack_preprocess_imputer - impute data
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9 mlpack_preprocess_imputer -i string -m string -s string [-c double] [-d int] [-V bool] [-o string] [-h -v]
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12 This utility takes a dataset and converts user defined missing variable
13 to another to provide more meaningful analysis
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15 The program does not modify the original file, but instead makes a sep‐
16 arate file to save the output data; You can save the output by specify‐
17 ing the file name with --output_file (-o).
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19 For example, if we consider 'NULL' in dimension 0 to be a missing vari‐
20 able and want to delete whole row containing the NULL in the column-
21 wise dataset, and save the result to result.csv, we could run
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23 $ mlpack_preprocess_imputer -i dataset.csv -o result.csv -m NULL -d 0 >
24 -s listwise_deletion
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27 --input_file (-i) [string]
28 File containing data.
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30 --missing_value (-m) [string]
31 User defined missing value.
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33 --strategy (-s) [string]
34 imputation strategy to be applied. Strategies should be one of
35 'custom', 'mean', 'median', and 'listwise_deletion'.
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38 --custom_value (-c) [double] User-defined custom imputation value.
39 Default value 0.
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41 --dimension (-d) [int]
42 The dimension to apply imputation to. Default value 0.
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44 --help (-h) [bool]
45 Default help info.
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47 --info [string]
48 Get help on a specific module or option. Default value ''.
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50 --verbose (-v) [bool]
51 Display informational messages and the full list of parameters
52 and timers at the end of execution.
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54 --version (-V) [bool]
55 Display the version of mlpack.
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58 --output_file (-o) [string]
59 File to save output into. Default value ''.
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62 For further information, including relevant papers, citations, and the‐
63 ory, consult the documentation found at http://www.mlpack.org or
64 included with your distribution of mlpack.
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68mlpack-3.0.4 21 February 2019 mlpack_preprocess_imputer(1)