[REVIEW]: mlpack 4: a fast, header-only C++ machine learning library

editorialbot commented 1 year ago

Submitting author: !--author-handle-->@rcurtin@osorensen<!--end-editor-- Reviewers: @sandeep-ps, @zhangjy-ge Archive: 10.5281/zenodo.7587252

Status

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Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@sandeep-ps & @zhangjy-ge, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review. First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @osorensen know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @sandeep-ps

📝 Checklist for @zhangjy-ge

editorialbot commented 1 year ago

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

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editorialbot commented 1 year ago

Software report:

github.com/AlDanial/cloc v 1.88  T=2.49 s (648.4 files/s, 148650.4 lines/s)
-------------------------------------------------------------------------------------
Language                           files          blank        comment           code
-------------------------------------------------------------------------------------
C/C++ Header                        1194          29525          70231         132436
C++                                  266          17996          24091          65742
Markdown                              48           3033              1          10745
CMake                                 60            734           1257           7159
Python                                 7            350            457           1459
Go                                     5            211            141           1114
YAML                                   8             82            103            531
Julia                                  1             88             55            335
Bourne Shell                           5             58             67            293
Cython                                 7             96            200            284
R                                      4             80             66            228
XML                                    3              0              0            211
TeX                                    1             23              0            189
CSS                                    1             19             11            121
JavaScript                             1              8             20             82
MSBuild script                         1              0              0             52
WiX source                             1              4              2             33
WiX string localization                1              1              0              6
-------------------------------------------------------------------------------------
SUM:                                1614          52308          96702         221020
-------------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository

editorialbot commented 1 year ago

Wordcount for paper.md is 1283

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

sandeep-ps commented 1 year ago

Review checklist for @sandeep-ps

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/mlpack/mlpack?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@rcurtin) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

zhangjy-ge commented 1 year ago

Review checklist for @zhangjy-ge

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/mlpack/mlpack?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@rcurtin) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

zhangjy-ge commented 1 year ago

I have finished my initial review. I think overall, mlpack 4 is a well written package that has indicated great potential in the machine learning field, considering its good documentation, user friendliness, and the algorithms it implemented, etc. Thus, I would recommend it for publication after minor revision:

even though I understand that in mlpack's website, there are some comparisons between mlpack and other similar packages, it is not mentioned in the manuscript itself. I would suggest the authors to add such descriptions, based on the requirements of "State of the field" and "performance" in the checklist.

sandeep-ps commented 1 year ago

Hi, @osorensen,

Two authors listed in the paper (#5 and #9) are affiliated with the same institution I'm affiliated with. We are from different units and haven't collaborated in the past, and we do not know each other. I request that this conflict be waived. Please let me know if there is a different process for this. Thanks.

osorensen commented 1 year ago

Hi, @osorensen,

Two authors listed in the paper (#5 and #9) are affiliated with the same institution I'm affiliated with. We are from different units and haven't collaborated in the past, and we do not know each other. I request that this conflict be waived. Please let me know if there is a different process for this. Thanks.

Thanks for letting me know @sandeep-ps. I think this should be waived, but I'll ping the editor-in-chief @openjournals/dsais-eics to hear what they think.

gkthiruvathukal commented 1 year ago

@sandeep-ps Thanks for letting us know. I'm a bit reticent about waiving the COI because there are implications of reviewing work by others at your institution if you are both still employed there. I'd prefer that we seek a different reviewer and hope we can assign you to another submission where we need reviewers. Ok? Thank you for understanding.

@osorensen Please assign to a different reviewer and keep @sandeep-ps in mind for other assignments!

sandeep-ps commented 1 year ago

Okay. Sounds good. Thanks.

FYI, my request was based on the COI guidelines, specifically, this statement.

danielskatz commented 1 year ago

HI @sandeep-ps - thanks for bringing this up. You are correct in that it is a conflict, and that it could be waived if needed, but it's up the track editor to decide.

gkthiruvathukal commented 1 year ago

Ok, @sandeep-ps, since you can attest that you are in a large organization and unlikely to be in contact with the individual profesionally, I am willing to grant the waiver. Given that we also have some independent feedback from the other reviewer, I think this might be ok. Let's proceed with you as a reviewer!

osorensen commented 1 year ago

Thanks @gkthiruvathukal. Then please continue with the review @sandeep-ps, and feel free to reach out to me if you have any questions about the review process.

sandeep-ps commented 1 year ago

Thanks, @gkthiruvathukal, @danielskatz, and @osorensen. I will continue with the review then.

rcurtin commented 1 year ago

I am not sure of the exact process, but when should I start responding to the review comments? Should I wait for @sandeep-ps's review to be complete? It would be straightforward to add some comparisons with other machine learning libraries, so I'm happy to do that.

osorensen commented 1 year ago

Thanks for asking @rcurtin. You're welcome and encouraged to start responding immediately.

sandeep-ps commented 1 year ago

@rcurtin, to give a progress update, since I had not used this library before, I was going through the installation process and checking out some of the functionality. I ran into some issues during that step last week, and I will be continuing my review this week.

rcurtin commented 1 year ago

I have finished my initial review. I think overall, mlpack 4 is a well written package that has indicated great potential in the machine learning field, considering its good documentation, user friendliness, and the algorithms it implemented, etc. Thus, I would recommend it for publication after minor revision:
1. even though I understand that in mlpack's website, there are some comparisons between mlpack and other similar packages, it is not mentioned in the manuscript itself. I would suggest the authors to add such descriptions, based on the requirements of "State of the field" and "performance" in the checklist.

@zhangjy-ge We do have some benchmarks on the homepage of the website. We can reference them more prominently in the paper---or do you mean to include some benchmarks specifically in the paper itself? (Personally I think it might be too long with a benchmarking table and sufficient description.)

@rcurtin, to give a progress update, since I had not used this library before, I was going through the installation process and checking out some of the functionality. I ran into some issues during that step last week, and I will be continuing my review this week.

@sandeep-ps happy to help out, just send a ping if you are having any issues. (You could even open an issue on mlpack's Github if you wanted, but whatever way is fine.) Often it can be easier to install mlpack via the system package manager, but our recent refactorings to make mlpack header-only have made the process much easier than it used to be.

zhangjy-ge commented 1 year ago

@rcurtin After double check, it seems a performance comparison is optional but we should still explicitly state the difference between mlpack and other packages (from Do the authors describe how this software compares to other commonly-used packages?) So maybe a short description of mlpack's differences comparing to other packages will be helpful.

sandeep-ps commented 1 year ago

I have also completed my initial review. In general, mlpack 4.0.0 is a well-written machine-learning library with good documentation, examples, community guidelines, etc.

Apart from zhangjy-ge's comment above, which I agree with, I have opened a few GitHub issues in the mlpack repository for further clarification and adding some missing content. I'm looking forward to more discussion on individual issues. Thanks.

osorensen commented 1 year ago

Thanks @sandeep-ps. @rcurtin feel free to ping me if you have any questions, and also report back in this thread once the issues in the source repo open by @sandeep-ps have been addressed.

rcurtin commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

rcurtin commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

rcurtin commented 1 year ago

Thanks for all of the comments @sandeep-ps and @zhangjy-ge! We have addressed each of them by resolving the various issues in the mlpack repository, and we added a paragraph to the Statement of Need section comparing mlpack with other C++ machine learning libraries. :+1:

sandeep-ps commented 1 year ago

Thanks for making the changes, @rcurtin.

sandeep-ps commented 1 year ago

The changes look good to me. I have completed my review and updated the checklist. Thanks for the opportunity to review this software paper.

zhangjy-ge commented 1 year ago

Thanks for the update. I also agree it is now good for publication.

osorensen commented 1 year ago

@editorialbot check references

osorensen commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

editorialbot commented 1 year ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- None

MISSING DOIs

- 10.21105/joss.00726 may be a valid DOI for title: mlpack 3: a fast, flexible machine learning library
- 10.1126/science.aaa8415 may be a valid DOI for title: Machine learning: Trends, perspectives, and prospects
- 10.1145/3219819.3220124 may be a valid DOI for title: Training big random forests with little resources
- 10.1145/3533378 may be a valid DOI for title: Challenges in deploying machine learning: a survey of case studies
- 10.21203/rs.3.rs-133138/v1 may be a valid DOI for title: Technology readiness levels for machine learning systems
- 10.3390/make3010004 may be a valid DOI for title: AI System Engineering—Key Challenges and Lessons Learned
- 10.1007/978-3-319-46759-7_17 may be a valid DOI for title: Fast approximate furthest neighbors with data-dependent candidate selection
- 10.1002/sam.11218 may be a valid DOI for title: Dual-tree fast exact max-kernel search
- 10.21105/joss.00026 may be a valid DOI for title: Armadillo: a template-based C++ library for linear algebra
- 10.1137/141000671 may be a valid DOI for title: Julia: A fresh approach to numerical computing
- 10.1109/tbdata.2019.2921572 may be a valid DOI for title: Billion-scale similarity search with GPUs
- 10.5220/0001787803310340 may be a valid DOI for title: Fast approximate nearest neighbors with automatic algorithm configuration

INVALID DOIs

- None

osorensen commented 1 year ago

@rcurtin, I have now read through the manuscript, and have only one editorial comment.

When citing multiple reference, please use the notation [@author1:2001; @author2:2001] as in the example paper.

For example, on line 26 we see the following

This happens because you write [@jordan2015machine] [@carleo2019machine] in the paper.

That is, please change to [@jordan2015machine; @carleo2019machine] in this case, and similarly all other places in the paper where multiple references appear next to each other.

When done, I'm ready to recommend acceptance of the paper.

rcurtin commented 1 year ago

Ah! The semicolon is the trick. I was trying to play with that earlier and didn't figure out how. Clearly I did not read the example paper closely enough, since it's documented quite clearly.

Anyway, I pushed fixes for all instances where this happened. I'll ask editorialbot to build again. :+1:

rcurtin commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

osorensen commented 1 year ago

Thanks @rcurtin.

At this point could you:

[ ] Make a tagged release of your software, and list the version tag of the archived version here.
[ ] Archive the reviewed software in Zenodo or a similar service (e.g., figshare, an institutional repository)
[ ] Check the archival deposit (e.g., in Zenodo) has the correct metadata. This includes the title (should match the paper title) and author list (make sure the list is correct and people who only made a small fix are not on it). You may also add the authors' ORCID.
[ ] Please list the DOI of the archived version here.

I can then move forward with recommending acceptance of the submission.

rcurtin commented 1 year ago

Tagged version of software: 4.0.1 link
Archived version in Zenodo: https://zenodo.org/record/7587252
Title, author list, and ORCIDs on the Zenodo archive are correct.
Archive DOI: 10.5281/zenodo.7587252

I did realize I forgot to pull one commit update to the paper. That's done now. So the version generated yesterday was incorrect. I'll have editorialbot generate it again.

Thanks so much! Let me know if anything else is needed.

rcurtin commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

osorensen commented 1 year ago

@editorialbot set 10.5281/zenodo.7587252 as archive

editorialbot commented 1 year ago

Done! Archive is now 10.5281/zenodo.7587252

osorensen commented 1 year ago

@editorialbot set 4.0.1 as release

editorialbot commented 1 year ago

I'm sorry human, I don't understand that. You can see what commands I support by typing:

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osorensen commented 1 year ago

@editorialbot set 4.0.1 as version

editorialbot commented 1 year ago

Done! version is now 4.0.1

osorensen commented 1 year ago

@editorialbot recommend-accept

editorialbot commented 1 year ago

Attempting dry run of processing paper acceptance...

openjournals / joss-reviews