[PRE REVIEW]: IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX

[editorialbot]

Submitting author: !--author-handle-->@Sm00thix<!--end-author-handle-- (Ole-Christian Galbo Engstrøm) Repository: https://github.com/Sm00thix/IKPLS Branch with paper.md (empty if default branch): Version: v1.0.1 Editor: !--editor-->@boisgera<!--end-editor-- Reviewers: @parmentelat, @basileMarchand Managing EiC: Arfon Smith

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Thanks for submitting your paper to JOSS @Sm00thix. Currently, there isn't a JOSS editor assigned to your paper.

@Sm00thix if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.08 s (517.2 files/s, 100134.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          18            895           1936           4076
TeX                              1             20              0            188
YAML                             7             24             14            150
reStructuredText                10             73             61            123
Markdown                         1             30              0             76
DOS Batch                        1              8              1             26
TOML                             1              2              0             21
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            40           1056           2019           4669
-------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1471

[editorialbot]

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

[editorialbot]

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[editorialbot]

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

OK DOIs

- None

MISSING DOIs

- 10.1016/s0169-7439(01)00155-1 may be a valid DOI for title: PLS-regression: a basic tool of chemometrics
- 10.1002/(sici)1099-128x(199701)11:1<73::aid-cem435>3.0.co;2-# may be a valid DOI for title: Improved PLS algorithms
- 10.1016/j.trac.2009.07.007 may be a valid DOI for title: Review of the most common pre-processing techniques for near-infrared spectra
- 10.1007/978-981-15-8648-4_7 may be a valid DOI for title: NIR Data Exploration and Regression by Chemometrics—A Primer
- 10.1111/1541-4337.12958 may be a valid DOI for title: Quantitative assessment of wheat quality using near-infrared spectroscopy: A comprehensive review
- 10.1007/s00362-009-0251-7 may be a valid DOI for title: Comparison of PLS algorithms when number of objects is much larger than number of variables
- 10.1002/cem.1248 may be a valid DOI for title: A comparison of nine PLS1 algorithms
- 10.1109/iccvw60793.2023.00055 may be a valid DOI for title: Improving Deep Learning on Hyperspectral Images of Grain by Incorporating Domain Knowledge from Chemometrics
- 10.1177/09670335221078356 may be a valid DOI for title: Hyperspectral imaging for classification of bulk grain samples with deep convolutional neural networks
- 10.1002/cem.3141 may be a valid DOI for title: Orders of magnitude speed increase in partial least squares feature selection with new simple indexing technique for very tall data sets
- 10.1002/cem.3201 may be a valid DOI for title: Much faster cross-validation in PLSR-modelling by avoiding redundant calculations
- 10.21105/joss.01190 may be a valid DOI for title: Multiblock PLS: Block dependent prediction modeling for Python

INVALID DOIs

- None

[Sm00thix]

From the list of reviewers I found three who seem particularly well-suited based on their interests and expertise - especially in the area of chemometrics. I mention them by GitHub username without tagging them. They are listed in no particular order:

• Kastakin
• diegoona
• olivertomic

[arfon]

@Sm00thix - thanks for your submission to JOSS. We're currently managing a large backlog of submissions and the editor most appropriate for your area is already rather busy.

For now, we will need to waitlist this paper and process it as the queue reduces. Thanks for your patience!

[arfon]

@editorialbot invite @boisgera as editor

:wave: @boisgera – would you be willing to edit this submission for JOSS?

[editorialbot]

Invitation to edit this submission sent!

[boisgera]

@editorialbot invite @boisgera as editor

👋 @boisgera – would you be willing to edit this submission for JOSS?

Yes, sure!

[arfon]

@editorialbot assign @boisgera as editor

Thanks @boisgera!

[editorialbot]

Assigned! @boisgera is now the editor

[Sm00thix]

@boisgera thank you for agreeing to be editor. I have realized that I want to make a slight change to some of my code to improve usability. Am I allowed to do so or will it interfere with the review process?

[boisgera]

@boisgera thank you for agreeing to be editor. I have realized that I want to make a slight change to some of my code to improve usability. Am I allowed to do so or will it interfere with the review process?

Hi @Sm00thix,

Sure, go ahead.

[Sm00thix]

Thank you, @boisgera. I have now updated the main branch with my desired changes. Specifically, I included the option to center and/or scale the input data directly in the models. I have updated the documentation, tests, and examples to reflect the changes. I have also released the new version of the package on PyPI. The paper remains unchanged. Now, I am ready to continue with the peer review process.

[Sm00thix]

Hi again, I made some additional updates to the code. I updated the type annotations and added typeguard to the tests to verify the annotations. The documentation and package have been updated accordingly.

[boisgera]

Hi again, I made some additional updates to the code. I updated the type annotations and added typeguard to the tests to verify the annotations. The documentation and package have been updated accordingly.

OK, great! I am currently contacting potential reviewers for your paper ; I'll let you know as soon 2-3 of them are willing to make the review.

[Sm00thix]

Hi again, I made some additional updates to the code. I updated the type annotations and added typeguard to the tests to verify the annotations. The documentation and package have been updated accordingly.

OK, great! I am currently contacting potential reviewers for your paper ; I'll let you know as soon 2-3 of them are willing to make the review.

Sounds good, thank you! I look forward to it.

[boisgera]

@parmentelat has accepted to review your paper; thank you Thierry! 🙏 I'm going to widen a bit the set of potential reviewers that I have contacted to find another person. Some of my initial contacts were not available but gave me good leads.

[Sm00thix]

@parmentelat has accepted to review your paper; thank you Thierry! 🙏

I'm going to widen a bit the set of potential reviewers that I have contacted to find another person. Some of my initial contacts were not available but gave me good leads.

Thank you for the update, @boisgera, and thank you @parmentelat 🥳

[boisgera]

@basileMarchand has accepted to review your papier; thank you Basile! 🙏

I'd like to wait a few days to make sure that no other potential reviewers shows up, then we'll start the review.

[boisgera]

@editorialbot add @parmentelat as reviewer

[editorialbot]

@parmentelat added to the reviewers list!

[boisgera]

@editorialbot add @basileMarchand as reviewer

[editorialbot]

@basileMarchand added to the reviewers list!

[Sm00thix]

Sounds good, @boisgera - thank you for the update. And thank you, @basileMarchand for agreeing to review!

[boisgera]

@editorialbot start review

[editorialbot]

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/6533.