Skip to content

Conversation

VincentAuriau
Copy link
Collaborator

No description provided.

Copy link
Contributor

Summary of Changes

Hello @VincentAuriau, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request integrates an official citation for a research paper related to basket choice modeling, ensuring proper attribution and referencing. Simultaneously, it expands the project's documentation by adding new entries and dedicated pages for the 'Bakery' and 'Badminton' datasets, enhancing the overall resource availability and user experience.

Highlights

  • New Official Citation: An official BibTeX citation for the paper 'Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling' has been added to the project, making it easier for users to reference this work.
  • Documentation Enhancement: The project's documentation has been updated to include references to the new citation and to introduce two new datasets, 'The Bakery Dataset' and 'The Badminton Dataset', improving their discoverability.
  • New Dataset Documentation: Dedicated documentation files have been created for 'The Bakery Dataset' and 'The Badminton Dataset', providing specific reference pages for these resources.
Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature Command Description
Code Review /gemini review Performs a code review for the current pull request in its current state.
Pull Request Summary /gemini summary Provides a summary of the current pull request in its current state.
Comment @gemini-code-assist Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help /gemini help Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

  1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution.

Copy link
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

This pull request adds the official citation for the AleaCarta paper, including a new CITATION_AC.bib file and updates to the README.md. It also adds documentation for the Bakery and Badminton datasets. My review focuses on ensuring the accuracy of the new citation information. I've found some inconsistencies with the publication year and conference details based on the provided DOI, and have suggested corrections to ensure users can cite the work accurately.

Comment on lines +1 to +9
@inproceedings{Desir2025
doi = {10.1007/978-3-032-06118-8_8},
url = {https://doi.org/10.1007/978-3-032-06118-8_8},
publisher = {Springer Nature Switzerland},
author = {Jules D{\'e}sir and Vincent Auriau and Martin Mo{\v{z}}ina and Emmanuel Malherbe},
title = {Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling},
booktitle={Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2025.},
year={2026}
}
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

There are several inconsistencies in the BibTeX entry. According to the provided DOI, the paper was published in 2024 for the ECML PKDD 2024 conference. The citation key, year, and booktitle should be updated to reflect the correct publication information. This will ensure users cite the work correctly.

@inproceedings{Desir2024,
  doi = {10.1007/978-3-032-06118-8_8},
  url = {https://doi.org/10.1007/978-3-032-06118-8_8},
  publisher = {Springer Nature Switzerland},
  author = {Jules D\'e'sir and Vincent Auriau and Martin Mo\'v'zina and Emmanuel Malherbe},
  title = {Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling},
  booktitle={Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2024.},
  year={2024}
}

Comment on lines +297 to +303
doi = {10.1007/978-3-032-06118-8_8},
url = {https://doi.org/10.1007/978-3-032-06118-8_8},
publisher = {Springer Nature Switzerland},
author = {Jules D{\'e}sir and Vincent Auriau and Martin Mo{\v{z}}ina and Emmanuel Malherbe},
title = {Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling},
booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
year={2025},
organization={Springer}
booktitle={Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2025.},
year={2026}
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

There are inconsistencies in this BibTeX entry. According to the provided DOI, the paper was published in 2024 for the ECML PKDD 2024 conference. The year and booktitle should be updated to reflect the correct publication information. For consistency, you might also want to update the citation key on line 296 to Desir2024.

Suggested change
doi = {10.1007/978-3-032-06118-8_8},
url = {https://doi.org/10.1007/978-3-032-06118-8_8},
publisher = {Springer Nature Switzerland},
author = {Jules D{\'e}sir and Vincent Auriau and Martin Mo{\v{z}}ina and Emmanuel Malherbe},
title = {Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling},
booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
year={2025},
organization={Springer}
booktitle={Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2025.},
year={2026}
doi = {10.1007/978-3-032-06118-8_8},
url = {https://doi.org/10.1007/978-3-032-06118-8_8},
publisher = {Springer Nature Switzerland},
author = {Jules D\'e'sir and Vincent Auriau and Martin Mo\'v'zina and Emmanuel Malherbe},
title = {Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling},
booktitle={Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2024.},
year={2024}

Copy link
Contributor

github-actions bot commented Oct 1, 2025

Coverage

Coverage Report for Python 3.9
FileStmtsMissCoverMissing
choice_learn
   __init__.py20100% 
   tf_ops.py62198%283
choice_learn/basket_models
   __init__.py40100% 
   alea_carta.py1362185%84–88, 90–94, 96–100, 104, 107, 129, 157, 418–443
   base_basket_model.py2111792%110–111, 122, 140, 183, 252, 353, 458, 555–557, 644, 724, 766–767, 867–868
   basic_attention_model.py78495%408, 411, 417, 424
   shopper.py171796%130, 159, 325, 345, 360, 363, 377
choice_learn/basket_models/data
   __init__.py20100% 
   basket_dataset.py137795%71–74, 369, 534, 573
   preprocessing.py947817%43–45, 128–364
choice_learn/basket_models/datasets
   __init__.py30100% 
   bakery.py38392%47, 51, 61
   synthetic_dataset.py72692%54, 158–163, 203
choice_learn/basket_models/utils
   __init__.py00100% 
   permutation.py22195%37
choice_learn/data
   __init__.py30100% 
   choice_dataset.py6493395%198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
   indexer.py2412390%20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
   storage.py161696%22, 33, 51, 56, 61, 71
   store.py72720%3–275
choice_learn/datasets
   __init__.py40100% 
   base.py400599%42–43, 153–154, 714
   expedia.py1028319%37–301
   tafeng.py490100% 
choice_learn/datasets/data
   __init__.py00100% 
choice_learn/models
   __init__.py14286%15–16
   base_model.py2691594%144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439, 540, 654–655
   baseline_models.py490100% 
   conditional_logit.py2692690%49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
   halo_mnl.py124298%186, 374
   latent_class_base_model.py2863986%55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
   latent_class_mnl.py62690%257–261, 296
   learning_mnl.py67396%157, 182, 188
   nested_logit.py2911296%55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
   reslogit.py132695%285, 360, 369, 374, 382, 432
   rumnet.py236399%748–751, 982
   simple_mnl.py139696%167, 275, 347, 355, 357, 359
   tastenet.py94397%142, 180, 188
choice_learn/toolbox
   __init__.py00100% 
   assortment_optimizer.py27678%28–30, 93–95, 160–162
   gurobi_opt.py2362360%3–675
   or_tools_opt.py2301195%103, 107, 296–305, 315, 319, 607, 611
TOTAL523874386% 

Tests Skipped Failures Errors Time
213 0 💤 0 ❌ 0 🔥 7m 58s ⏱️

Copy link
Contributor

github-actions bot commented Oct 1, 2025

Coverage

Coverage Report for Python 3.10
FileStmtsMissCoverMissing
choice_learn
   __init__.py20100% 
   tf_ops.py62198%283
choice_learn/basket_models
   __init__.py40100% 
   alea_carta.py1362185%84–88, 90–94, 96–100, 104, 107, 129, 157, 418–443
   base_basket_model.py2111792%110–111, 122, 140, 183, 252, 353, 458, 555–557, 644, 724, 766–767, 867–868
   basic_attention_model.py78495%408, 411, 417, 424
   shopper.py171796%130, 159, 325, 345, 360, 363, 377
choice_learn/basket_models/data
   __init__.py20100% 
   basket_dataset.py137795%71–74, 369, 534, 573
   preprocessing.py947817%43–45, 128–364
choice_learn/basket_models/datasets
   __init__.py30100% 
   bakery.py38392%47, 51, 61
   synthetic_dataset.py72692%54, 158–163, 203
choice_learn/basket_models/utils
   __init__.py00100% 
   permutation.py22195%37
choice_learn/data
   __init__.py30100% 
   choice_dataset.py6493395%198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
   indexer.py2412390%20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
   storage.py161696%22, 33, 51, 56, 61, 71
   store.py72720%3–275
choice_learn/datasets
   __init__.py40100% 
   base.py400599%42–43, 153–154, 714
   expedia.py1028319%37–301
   tafeng.py490100% 
choice_learn/datasets/data
   __init__.py00100% 
choice_learn/models
   __init__.py14286%15–16
   base_model.py2691594%144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439, 540, 654–655
   baseline_models.py490100% 
   conditional_logit.py2692690%49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
   halo_mnl.py124298%186, 374
   latent_class_base_model.py2863986%55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
   latent_class_mnl.py62690%257–261, 296
   learning_mnl.py67396%157, 182, 188
   nested_logit.py2911296%55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
   reslogit.py132695%285, 360, 369, 374, 382, 432
   rumnet.py236399%748–751, 982
   simple_mnl.py139696%167, 275, 347, 355, 357, 359
   tastenet.py94397%142, 180, 188
choice_learn/toolbox
   __init__.py00100% 
   assortment_optimizer.py27678%28–30, 93–95, 160–162
   gurobi_opt.py2382380%3–675
   or_tools_opt.py2301195%103, 107, 296–305, 315, 319, 607, 611
TOTAL524074586% 

Tests Skipped Failures Errors Time
213 0 💤 1 ❌ 0 🔥 8m 7s ⏱️

Copy link
Contributor

github-actions bot commented Oct 1, 2025

Coverage

Coverage Report for Python 3.11
FileStmtsMissCoverMissing
choice_learn
   __init__.py20100% 
   tf_ops.py62198%283
choice_learn/basket_models
   __init__.py40100% 
   alea_carta.py1362185%84–88, 90–94, 96–100, 104, 107, 129, 157, 418–443
   base_basket_model.py2111792%110–111, 122, 140, 183, 252, 353, 458, 555–557, 644, 724, 766–767, 867–868
   basic_attention_model.py78495%408, 411, 417, 424
   shopper.py171796%130, 159, 325, 345, 360, 363, 377
choice_learn/basket_models/data
   __init__.py20100% 
   basket_dataset.py137795%71–74, 369, 534, 573
   preprocessing.py947817%43–45, 128–364
choice_learn/basket_models/datasets
   __init__.py30100% 
   bakery.py38392%47, 51, 61
   synthetic_dataset.py72692%54, 158–163, 203
choice_learn/basket_models/utils
   __init__.py00100% 
   permutation.py22195%37
choice_learn/data
   __init__.py30100% 
   choice_dataset.py6493395%198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
   indexer.py2412390%20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
   storage.py161696%22, 33, 51, 56, 61, 71
   store.py72720%3–275
choice_learn/datasets
   __init__.py40100% 
   base.py400599%42–43, 153–154, 714
   expedia.py1028319%37–301
   tafeng.py490100% 
choice_learn/datasets/data
   __init__.py00100% 
choice_learn/models
   __init__.py14286%15–16
   base_model.py2691594%144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439, 540, 654–655
   baseline_models.py490100% 
   conditional_logit.py2692690%49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
   halo_mnl.py1241885%186, 341, 360, 364–380
   latent_class_base_model.py2863986%55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
   latent_class_mnl.py62690%257–261, 296
   learning_mnl.py67396%157, 182, 188
   nested_logit.py2911296%55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
   reslogit.py132695%285, 360, 369, 374, 382, 432
   rumnet.py236399%748–751, 982
   simple_mnl.py139696%167, 275, 347, 355, 357, 359
   tastenet.py94397%142, 180, 188
choice_learn/toolbox
   __init__.py00100% 
   assortment_optimizer.py27678%28–30, 93–95, 160–162
   gurobi_opt.py2382380%3–675
   or_tools_opt.py2301195%103, 107, 296–305, 315, 319, 607, 611
TOTAL524076185% 

Tests Skipped Failures Errors Time
213 0 💤 1 ❌ 0 🔥 8m 36s ⏱️

Copy link
Contributor

github-actions bot commented Oct 1, 2025

Coverage

Coverage Report for Python 3.12
FileStmtsMissCoverMissing
choice_learn
   __init__.py20100% 
   tf_ops.py62198%283
choice_learn/basket_models
   __init__.py40100% 
   alea_carta.py1362185%84–88, 90–94, 96–100, 104, 107, 129, 157, 418–443
   base_basket_model.py2111792%110–111, 122, 140, 183, 252, 353, 458, 555–557, 644, 724, 766–767, 867–868
   basic_attention_model.py78495%408, 411, 417, 424
   shopper.py171796%130, 159, 325, 345, 360, 363, 377
choice_learn/basket_models/data
   __init__.py20100% 
   basket_dataset.py137795%71–74, 369, 534, 573
   preprocessing.py947817%43–45, 128–364
choice_learn/basket_models/datasets
   __init__.py30100% 
   bakery.py38392%47, 53, 61
   synthetic_dataset.py72692%54, 158–163, 203
choice_learn/basket_models/utils
   __init__.py00100% 
   permutation.py22195%37
choice_learn/data
   __init__.py30100% 
   choice_dataset.py6493395%198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
   indexer.py2412390%20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
   storage.py161696%22, 33, 51, 56, 61, 71
   store.py72720%3–275
choice_learn/datasets
   __init__.py40100% 
   base.py400599%42–43, 153–154, 714
   expedia.py1028319%37–301
   tafeng.py490100% 
choice_learn/datasets/data
   __init__.py00100% 
choice_learn/models
   __init__.py14286%15–16
   base_model.py2691594%144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439, 540, 654–655
   baseline_models.py490100% 
   conditional_logit.py2692690%49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
   halo_mnl.py124298%186, 374
   latent_class_base_model.py2863986%55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
   latent_class_mnl.py62690%257–261, 296
   learning_mnl.py67396%157, 182, 188
   nested_logit.py2911296%55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
   reslogit.py132695%285, 360, 369, 374, 382, 432
   rumnet.py236399%748–751, 982
   simple_mnl.py139696%167, 275, 347, 355, 357, 359
   tastenet.py94397%142, 180, 188
choice_learn/toolbox
   __init__.py00100% 
   assortment_optimizer.py27678%28–30, 93–95, 160–162
   gurobi_opt.py2382380%3–675
   or_tools_opt.py2301195%103, 107, 296–305, 315, 319, 607, 611
TOTAL524074586% 

Tests Skipped Failures Errors Time
213 0 💤 0 ❌ 0 🔥 9m 5s ⏱️

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant