So, I have found an application which could benefit from a machine learning algorithm:
There is a pretty standard method in my area of research for design of experiments and I have discovered that one step could be automated to save time. The automation can be done with a variety of standard machine learning algorithms and I've selected one that:
- is used pretty often, according to literature
- provides very satisfactory results (high accuracy) on my data
I am currently writing a paper on my findings. My question is, how could I rule out the alternatives or at least justify my choice (for example, in the "related work" section) against other algorithms that could possibly work better/be more suitable?
Considering machine learning is not my strongest skill, I have tried to implement most of the other state-of-art algorithms to compare to, but for some of them I just don't have the knowledge to do so.
*My question is similar to this one: What's the best way to justify your choice of baseline methods for academic paper?, but the difference is that my paper's novelty is about the new application area, rather than a new algorithm.