Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 8 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org
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  • Scientific vocabulary similarity
    Low similarity (13.6%) to scientific vocabulary

Scientific Fields

Artificial Intelligence and Machine Learning Computer Science - 62% confidence
Last synced: 4 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: firefly-cpp
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 2.32 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 1
  • Open Issues: 2
  • Releases: 3
Created almost 2 years ago · Last pushed 4 months ago
Metadata Files
Readme License Code of conduct Citation

README.md

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NiaAutoARM

PyPI version PyPI - Python Version PyPI - Downloads Downloads NiaAutoARM

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🔍 About💡 How it works?📦 Installation🚀 Usage📖 Further read📝 References🔑 License

A novel AutoML method for automatically constructing the full association rule mining pipelines based on stochastic population-based metaheuristics.

  • Free software: MIT license
  • Python: 3.9, 3.10, 3.11, 3.12

🔍 About

The numerical association rule mining paradigm that includes concurrent dealing with numerical and categorical attributes is beneficial for discovering associations from datasets that consist of both features. The process is not considered as easy since it incorporates several components that form an entire pipeline, i.e., preprocessing, algorithm selection, hyperparameter optimization, and the definition of metrics that evaluate the quality of the association rule. NiaAutoARM software aims to automatize this process and reduce the need for the user's effort to discover association rules.

💡 How it works?

See the following preprint for more information.

📦 Installation

pip

To install NiaAutoARM with pip, use:

sh pip install niaautoarm

🚀 Usage

Explore the examples directory for more information on how to use the NiaAutoARM package.

📖 Further read

[1] NiaARM.jl: Numerical Association Rule Mining in Julia

[2] arm-preprocessing: Implementation of several preprocessing techniques for Association Rule Mining (ARM)

📄 Cite us

Mlakar, U.; Fister, I., Jr.; Fister, I. NiaAutoARM: Automated Framework for Constructing and Evaluating Association Rule Mining Pipelines. Mathematics 2025, 13, 1957. https://doi.org/10.3390/math13121957

📝 References

[1] Ž. Stupan, Fister Jr., I. (2022). NiaARM: A minimalistic framework for Numerical Association Rule Mining. Journal of Open Source Software, 7(77), 4448.

[2] L. Pečnik, Fister, I., Fister, I. Jr. NiaAML2: An Improved AutoML Using Nature-Inspired Algorithms. In International Conference on Swarm Intelligence (pp. 243-252). Springer, Cham, 2021.

🔑 License

This package is distributed under the MIT License. This license can be found online at http://www.opensource.org/licenses/MIT.

Disclaimer

This framework is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!

Owner

  • Name: Iztok Fister Jr.
  • Login: firefly-cpp
  • Kind: user
  • Location: Slovenia

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this repository, please cite the following publication:"
title: "NiaAutoARM: Automated Framework for Constructing and Evaluating Association Rule Mining Pipelines"
authors:
  - family-names: Mlakar
    given-names: Uros
  - family-names: Fister
    given-names: Iztok Jr.
  - family-names: Fister
    given-names: Iztok
date-released: 2025-01-01
version: "1.0.0"
doi: "10.3390/math13121957"
url: "https://doi.org/10.3390/math13121957"
type: software

GitHub Events

Total
  • Create event: 5
  • Issues event: 1
  • Release event: 3
  • Delete event: 3
  • Issue comment event: 5
  • Push event: 17
  • Public event: 1
  • Pull request event: 11
  • Fork event: 3
Last Year
  • Create event: 5
  • Issues event: 1
  • Release event: 3
  • Delete event: 3
  • Issue comment event: 5
  • Push event: 17
  • Public event: 1
  • Pull request event: 11
  • Fork event: 3

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 4
  • Total pull requests: 21
  • Average time to close issues: 5 months
  • Average time to close pull requests: 25 days
  • Total issue authors: 2
  • Total pull request authors: 4
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.29
  • Merged pull requests: 15
  • Bot issues: 0
  • Bot pull requests: 12
Past Year
  • Issues: 4
  • Pull requests: 16
  • Average time to close issues: 5 months
  • Average time to close pull requests: about 8 hours
  • Issue authors: 2
  • Pull request authors: 4
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.31
  • Merged pull requests: 11
  • Bot issues: 0
  • Bot pull requests: 7
Top Authors
Issue Authors
  • firefly-cpp (3)
  • mlaky88 (1)
Pull Request Authors
  • dependabot[bot] (12)
  • lahovniktadej (6)
  • rhododendrom (2)
  • mlaky88 (1)
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dependencies (12) python (5)

Packages

  • Total packages: 6
  • Total downloads:
    • pypi 19 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 15
  • Total maintainers: 2
alpine-edge: py3-niaautoarm-doc

AutoML method for constructing the full ARM pipelines (documentation)

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Average: 6.6%
Dependent packages count: 13.2%
Maintainers (1)
Last synced: 4 months ago
alpine-edge: py3-niaautoarm-pyc

Precompiled Python bytecode for py3-niaautoarm

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Average: 7.0%
Dependent packages count: 14.0%
Maintainers (1)
Last synced: 4 months ago
alpine-edge: py3-niaautoarm

AutoML method for constructing the full ARM pipelines

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Average: 7.0%
Dependent packages count: 14.0%
Maintainers (1)
Last synced: 4 months ago
pypi.org: niaautoarm

Automated generation and evaluation of Association Rule Mining pipelines

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 19 Last month
Rankings
Dependent packages count: 9.8%
Average: 32.4%
Dependent repos count: 55.1%
Maintainers (1)
Last synced: 4 months ago
alpine-v3.22: py3-niaautoarm-pyc

Precompiled Python bytecode for py3-niaautoarm

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 100%
Maintainers (1)
Last synced: 4 months ago
alpine-v3.22: py3-niaautoarm

AutoML method for constructing the full ARM pipelines

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 100%
Maintainers (1)
Last synced: 4 months ago

Dependencies

.github/workflows/build.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
poetry.lock pypi
  • atomicwrites 1.4.1
  • attrs 22.2.0
  • click 8.1.3
  • colorama 0.4.6
  • contourpy 1.0.7
  • cycler 0.11.0
  • et-xmlfile 1.1.0
  • fonttools 4.38.0
  • importlib-resources 5.12.0
  • joblib 1.2.0
  • kiwisolver 1.4.4
  • matplotlib 3.7.0
  • more-itertools 9.0.0
  • niaaml 1.1.11
  • niaarm 0.3.1
  • niapy 2.0.4
  • nltk 3.9
  • numpy 1.24.2
  • openpyxl 3.1.1
  • packaging 23.0
  • pandas 1.5.3
  • pillow 10.3.0
  • pluggy 0.13.1
  • py 1.11.0
  • pyparsing 3.0.9
  • pytest 5.4.3
  • python-dateutil 2.8.2
  • pytz 2022.7.1
  • regex 2022.10.31
  • scikit-learn 1.5.0
  • scipy 1.9.3
  • six 1.16.0
  • threadpoolctl 3.1.0
  • tqdm 4.66.3
  • wcwidth 0.2.6
  • zipp 3.19.1
pyproject.toml pypi
  • pytest ^5.2 develop
  • niaarm ^0.3.12
  • niapy ^2.0.5
  • pandas ^2.1.1
  • python ^3.9