<p>In <a href="https://github.com/mlpack/mlpack/pull/694#discussion_r68357573">src/mlpack/core/data/imputation_methods/mean_imputation.hpp</a>:</p>
<pre style='color:#555'>> + double sum;
> + size_t elems = 0; // excluding nan or missing target
> +
> + using PairType = std::pair<size_t, size_t>;
> + // dimensions and indexes are saved as pairs inside this vector.
> + std::vector<PairType> targets;
> +
> + // calculate number of elements and sum of them excluding mapped value or
> + // nan. while doing that, remember where mappedValue or NaN exists.
> + if (transpose)
> + {
> + for (size_t i = 0; i < input.n_rows; ++i)
> + {
> + if (input(i, dimension) == mappedValue)
> + {
> + targets.push_back(std::make_pair(i, dimension));
</pre>
<p>Another approach(maybe you already know)--targets.emplace_back(i, dimension);</p>
<p>Different with push_back is emplace_back will construct the value directly,it may(or may not) provide better performance. Pick the one you like :)</p>
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