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I am writing a paper in computer science literature. I have a method that has two main parameters. It turns out that one of these parameters does not have a significant impact on the quality of the results, but it has a big impact on the efficiency of the method. I have a question:

  • How should I explain this in my experimental results section? Should I draw some plots and show that for different variation of this parameter the result is the same (this seems numb to draw some plots that all overlap) or I should write a paragraph and explain this phenomenon?
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  • This is, afaik, known as sensitivity analysis. Surely, other papers before have had to deal with the issue of how to present the fact that the model isn't sensitive to a specific parameter? – xLeitix Nov 7 '14 at 9:58
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Actually, I had a programming part in my masters thesis in which I wanted to show that some parameters do not have significant impact on the results. This is what I did which seems to be a combination of your methods:

I drew a plot with all the parameter remaining the same except one parameter that I want to study on. Even if the variation of the parameter does not show any significant change in the results, it does worth to show the results in a plot. It is not important that all the lines overlap. At least the reader sees that the results are the same. But, in a paragraph or at least one sentence following the graph I would talk about this. You may write that all the plots overlap, because of this and because of that; and talk about why such results happen. Also, in the caption of the plot, write something that directly says something about such insignificance.

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    I absolutely agree. I love seeing plots with a whole bunch of overlapping flat lines that essentially say "We hit our method with all sorts of hammers, and it didn't budge!" – jakebeal Nov 7 '14 at 13:24

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