<p>In <a href="https://github.com/mlpack/mlpack/pull/694#discussion_r71871714">src/mlpack/core/data/imputation_methods/mean_imputation.hpp</a>:</p>
<pre style='color:#555'>> + {
> + output(target.first, target.second) = mean;
> + }
> + }
> +
> + /**
> + * Impute function searches through the input looking for mappedValue and
> + * replaces it with the mean of the given dimension. The result is overwritten
> + * to the input matrix.
> + *
> + * @param input Matrix that contains mappedValue.
> + * @param mappedValue Value that the user wants to get rid of.
> + * @param dimension Index of the dimension of the mappedValue.
> + * @param columnMajor State of whether the input matrix is columnMajor or not.
> + */
> + void Impute(arma::Mat<T>& input,
</pre>
<p>I wanted to reuse the codes of the overloads, but <br>
Impute(input, input, ...) searches through all values inside the matrix (to produce output), while Impute(input) searches through only with the given dimension.<br>
It would not be very efficient. What do you think?</p>
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