<p>In <a href="https://github.com/mlpack/mlpack/pull/694#discussion_r70025047">src/mlpack/methods/preprocess/preprocess_imputer_main.cpp</a>:</p>
<pre style='color:#555'>&gt; +    &quot;separate file to save the output data; The program requires you to &quot;
&gt; +    &quot;specify the file name with --output_file (-o).&quot;
&gt; +    &quot;\n\n&quot;
&gt; +    &quot;For example, if we consider &#39;NULL&#39; in dimension 0 to be a missing &quot;
&gt; +    &quot;variable and want to delete whole row containing the NULL in the &quot;
&gt; +    &quot;column-wise dataset, and save the result to result.csv, we could run&quot;
&gt; +    &quot;\n\n&quot;
&gt; +    &quot;$ mlpack_preprocess_imputer -i dataset.csv -o result.csv -m NULL -d 0 \n&quot;
&gt; +    &quot;&gt; -s listwise_deletion&quot;)
&gt; +
&gt; +PARAM_STRING_REQ(&quot;input_file&quot;, &quot;File containing data,&quot;, &quot;i&quot;);
&gt; +PARAM_STRING(&quot;output_file&quot;, &quot;File to save output&quot;, &quot;o&quot;, &quot;&quot;);
&gt; +PARAM_STRING(&quot;missing_value&quot;, &quot;User defined missing value&quot;, &quot;m&quot;, &quot;&quot;)
&gt; +PARAM_STRING(&quot;strategy&quot;, &quot;imputation strategy to be applied&quot;, &quot;s&quot;, &quot;&quot;)
&gt; +PARAM_DOUBLE(&quot;custom_value&quot;, &quot;user_defined custom value&quot;, &quot;c&quot;, 0.0)
&gt; +PARAM_INT(&quot;dimension&quot;, &quot;the dimension to apply imputation&quot;, &quot;d&quot;, 0);
</pre>
<p>Updated so that when --dimension is not specified, the program applies the imputation strategy to all dimensions.</p>

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