<p>In <a href="https://github.com/mlpack/mlpack/pull/694#discussion_r69922436">src/mlpack/core/data/imputation_methods/listwise_deletion.hpp</a>:</p>
<pre style='color:#555'>> + const T& mappedValue,
> + const size_t dimension,
> + const bool transpose = true)
> + {
> + // initiate output
> + output = input;
> + size_t count = 0;
> +
> + if (transpose)
> + {
> + for (size_t i = 0; i < input.n_cols; ++i)
> + {
> + if (input(dimension, i) == mappedValue ||
> + std::isnan(input(dimension, i)))
> + {
> + output.shed_col(i - count);
</pre>
<p>I think that here is might be faster to collect the list of columns that needs to be dropped, and then use non-contiguous matrix views to extract what you need to keep. Something like this:</p>
<pre><code>std::vector<arma::uword> colsToKeep;
colsToKeep.push_back(0);
colsToKeep.push_back(2);
colsToKeep.push_back(3);
// Only keep columns 0, 2, and 3.
arma::mat output = input.cols(colsToKeep);
</code></pre>
<p>But before you commit that change, it is probably worth running some quick tests with <code>mlpack_preprocess_impute</code> to ensure that speeds things up. I think you will see a lot of speedup with large matrices.</p>
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