nim Composition Space Optimization is a high-performance tool leveraging metaprogramming to implement several methods for selecting components (data dimensions) in compositional datasets, as to optimize the data availability and density for applications such as machine learning.
Below are initial (itemized) JOSS review comments from @Henrium. I will progressively work on addressing them one-by-one here.
I have tested in both GitHub Codespaces and Linux, the package is easy to install and works as claimed.
Summary: I suggest the following to make it more accessible to "diverse, non-specialist audience": (1) introduce the background first, then what nimCSO is and what it does; (2) elaborate on the purpose and challenges.
State of field: What are some other approaches to compositional space optimization; are there relevant software? References should be added if applicable. It's not necessary to compare with them, but good to make the paper informative.
In quickstart.ipynb: the routine mostCommon is clear at first, but got confusing when it comes to "removing elements". What's the optimization objective of removing elements?
The "Algorithm-Based Search" method relies on an assumption, "elements present in already expanded ...", is it supported by any rationale, experiments, prior studies, etc.?
I didn't find "community guidelines", though it doesn't seem necessary here. Consider adding one?
Below are initial (itemized) JOSS review comments from @Henrium. I will progressively work on addressing them one-by-one here.
I have tested in both GitHub Codespaces and Linux, the package is easy to install and works as claimed.
Summary: I suggest the following to make it more accessible to "diverse, non-specialist audience": (1) introduce the background first, then what
nimCSO
is and what it does; (2) elaborate on the purpose and challenges.State of field: What are some other approaches to compositional space optimization; are there relevant software? References should be added if applicable. It's not necessary to compare with them, but good to make the paper informative.
In
quickstart.ipynb
: the routine mostCommon is clear at first, but got confusing when it comes to "removing elements". What's the optimization objective of removing elements?The "Algorithm-Based Search" method relies on an assumption, "elements present in already expanded ...", is it supported by any rationale, experiments, prior studies, etc.?
I didn't find "community guidelines", though it doesn't seem necessary here. Consider adding one?