<p>In <a href="https://github.com/mlpack/mlpack/pull/650#discussion_r64743312">src/mlpack/methods/preprocess/preprocess_split_main.cpp</a>:</p>
<pre style='color:#555'>> +#include <mlpack/core.hpp>
> +#include <mlpack/core/data/split_data.hpp>
> +
> +PROGRAM_INFO("Split into Train and Test Data", "This "
> + "utility takes data and labels and split into a training "
> + "set and a test set.");
> +
> +// Define parameters for data
> +PARAM_STRING_REQ("input_file", "File containing data,", "i");
> +PARAM_STRING_REQ("output_train_data", "File name to save train data", "d");
> +PARAM_STRING_REQ("output_test_data", "File name to save test data", "D");
> +
> +// Define parameters for labels
> +PARAM_STRING_REQ("input_label", "File containing labels", "I");
> +PARAM_STRING_REQ("output_train_label", "File name to save train label", "l");
> +PARAM_STRING_REQ("output_test_label", "File name to save test label", "L");
</pre>
<p>I think for consistency with other programs in mlpack I would go with parameters --training_file (-t), --training_labels_file (-l), --test_file (-T), and --test_labels_file (-L) for the output parameters.</p>
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