mlpack_preprocess_imputer1

Usage

Overview

This utility takes a dataset and converts a user-defined missing variable to another to provide more meaningful analysis.

The program does not modify the original file, but instead makes a separate file to save the output data; You can save the output by specifying the file name with'--output_file (-o)'.

For example, if we consider 'NULL' in dimension 0 to be a missing variable and want to delete whole row containing the NULL in the column-wise'dataset.csv', and save the result to 'result.csv', we could run :

$ mlpack_preprocess_imputer --input_file dataset --output_file result --missing_value NULL --dimension 0 --strategy listwise_deletion

Options

--input_file (-i) [string]

File containing data.

--missing_value (-m) [string]

User defined missing value.

--strategy (-s) [string]

imputation strategy to be applied. Strategies should be one of 'custom', 'mean', 'median', and 'listwise_deletion'.

Options

--custom_value (-c) [double] User-defined custom imputation value. Default value 0.

--dimension (-d) [int]

The dimension to apply imputation to. Default value 0.

--help (-h) [bool]

Default help info.

--info [string]

Print help on a specific option. Default value ''.

--verbose (-v) [bool]

Display informational messages and the full list of parameters and timers at the end of execution.

--version (-V) [bool]

Display the version of mlpack.

Options

--output_file (-o) [string]

File to save output into. Default value ''.

Additional information

For further information, including relevant papers, citations, and theory, consult the documentation found at http://www.mlpack.org or included with your distribution of mlpack.