.\" Text automatically generated by txt2man
.TH mlpack_preprocess_imputer  "26 December 2016" "" ""
.SH NAME
\fBmlpack_preprocess_imputer \fP- impute data
.SH SYNOPSIS
.nf
.fam C
 \fBmlpack_preprocess_imputer\fP [\fB-h\fP] [\fB-v\fP]  
.fam T
.fi
.fam T
.fi
.SH DESCRIPTION


This utility takes a dataset and converts user defined missing variable to
another to provide more meaningful analysis 
.PP
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 \fB--output_file\fP (\fB-o\fP).
.PP
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, and
save the result to result.csv, we could run
.PP
$ \fBmlpack_preprocess_imputer\fP \fB-i\fP dataset.csv \fB-o\fP result.csv \fB-m\fP NULL \fB-d\fP 0 
> \fB-s\fP listwise_deletion
.SH REQUIRED INPUT OPTIONS 

.TP
.B
\fB--input_file\fP (\fB-i\fP) [string]
File containing data,
.SH OPTIONAL INPUT OPTIONS 

\fB--custom_value\fP (\fB-c\fP) [double] user_defined custom value Default value 0.
.TP
.B
\fB--dimension\fP (\fB-d\fP) [int]
the dimension to apply imputation Default value
.RS
.IP 0. 4

.RE
.TP
.B
\fB--help\fP (\fB-h\fP)
Default help info.
.TP
.B
\fB--info\fP [string]
Get help on a specific module or option. 
Default value ''.
\fB--missing_value\fP (\fB-m\fP) [string] 
User defined missing value Default value ''.
.TP
.B
\fB--strategy\fP (\fB-s\fP) [string]
imputation strategy to be applied. Strategies
should be one of 'custom', 'mean', 'median', and
\(cqlistwise_deletion'. Default value ''.
.TP
.B
\fB--verbose\fP (\fB-v\fP)
Display informational messages and the full list
of parameters and timers at the end of
execution.
.TP
.B
\fB--version\fP (\fB-V\fP)
Display the version of mlpack.
.SH OPTIONAL OUTPUT OPTIONS 

.TP
.B
\fB--output_file\fP (\fB-o\fP) [string]
File to save output Default value ''.
.SH ADDITIONAL INFORMATION
.SH ADDITIONAL INFORMATION


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 MLPACK.