[PRE REVIEW]: GBNet: Gradient Boosting packages integrated into PyTorch

[editorialbot]

Submitting author: @mthorrell (Michael Horrell)
Repository: https://github.com/mthorrell/gbnet
Branch with paper.md (empty if default branch): paper
Version: v0.3.0
Editor: Pending
Reviewers: Pending
Managing EiC: Chris Vernon

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Software report:

github.com/AlDanial/cloc v 1.98  T=0.04 s (1062.7 files/s, 306387.7 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          17            473            599           1619
Jupyter Notebook                 3              0           8719            435
Markdown                         3            121              0            305
TeX                              1             19              0            159
YAML                             6             17             25            115
reStructuredText                 9             79            128             92
DOS Batch                        1              8              1             26
Text                             4              0              0             14
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            45            721           9479           2774
-------------------------------------------------------------------------------

Commit count by author:

    95	mthorrell
    46	Michael Horrell

[editorialbot]

Paper file info:

⚠️ Wordcount for paper.md is 1255

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

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

✅ OK DOIs

- 10.1145/2939672.2939785 is OK
- 10.1080/00031305.2017.1380080 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Regression Models for Ordinal Data
- No DOI given, and none found for title: Ordinal Regression
- No DOI given, and none found for title: Distributed representations of words and phrases a...
- No DOI given, and none found for title: Autoencoders, minimum description length and Helmh...
- No DOI given, and none found for title: Auto-encoding variational bayes
- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python
- No DOI given, and none found for title: LightGBM: A Highly Efficient Gradient Boosting Dec...
- No DOI given, and none found for title: 2021 Kaggle Machine Learning & Data Science Survey
- No DOI given, and none found for title: PyTorch: An Imperative Style, High-Performance Dee...
- No DOI given, and none found for title: Wide Boosting
- No DOI given, and none found for title: OrdinalGBT - Gradient Boosting for Ordinal Regress...
- No DOI given, and none found for title: DeepGBM: A deep learning framework distilled by GB...
- No DOI given, and none found for title: Neural Oblivious Decision Ensembles for Deep Learn...
- No DOI given, and none found for title: Neural decision trees

❌ MISSING DOIs

- 10.1214/aos/1013203451 may be a valid DOI for title: Greedy Function Approximation: A Gradient Boosting...
- 10.1109/iccv.2015.172 may be a valid DOI for title: Deep neural decision forests
- 10.1109/cvpr.2006.100 may be a valid DOI for title: Dimensionality reduction by learning an invariant ...

❌ INVALID DOIs

- None

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

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[mthorrell]

Possible reviewers:
Matteo Ravasi
Harish Varma Siravuri
Junjie Liu
YI HAN
James Patrick Horine