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caml

Source code for the paper "A Few Models to Rule Them All: Aggregating Machine Learning Models" at LWDA 2023

https://github.com/floriansiepe/caml

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
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    Low similarity (10.1%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Source code for the paper "A Few Models to Rule Them All: Aggregating Machine Learning Models" at LWDA 2023

Basic Info
  • Host: GitHub
  • Owner: floriansiepe
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 938 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 4
  • Releases: 0
Created over 2 years ago · Last pushed 12 months ago
Metadata Files
Readme License Citation

README.md

CAML

Source code for the paper "A Few Models to Rule Them All: Aggregating Machine Learning Models" at LWDA 2023.

Installation

bash poetry install poetry shell

Getting Started

See demo.py for a simple example.

This implementation of CAML currently supports time series forecasting models only provided by the Darts library. However, it can easily adapted for other libraries and model types (e.g. sklearn).

Adding model architectures

To add a new model architecture, you need to create a new class that inherits from ObjectiveFactory and implements the create and build_model methods. See also the prebuilt factories for examples.

Citation

If this is useful for your research, please consider citing the paper (PDF):

bibtex @inproceedings{Siepe2023, author = {Florian Siepe and Phillip Wenig and Thorsten Papenbrock}, title = {A Few Models to Rule Them All: Aggregating Machine Learning Models}, booktitle = {Proceedings of the Conference Lernen, Wissen, Daten, Analysen}, numpages = {12}, year = {2023}, series = {LWDA '23}, location = {Marburg, Germany}, publisher = {CEUR Workshop Proceedings}, url = {https://ceur-ws.org/XXXX} }

Owner

  • Name: Florian Siepe
  • Login: floriansiepe
  • Kind: user
  • Location: Marburg, Germany
  • Company: Viessmann IT Service

Software engineer from a little city somewhere in nowhere working with Java and Angular.

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it using these metadata."
title: "A Few Models to Rule Them All: Aggregating Machine Learning Models"
version: 1.0.0
date-released: 2023-10-09

authors:
  - family-names: "Siepe"
    given-names: "Florian"
  - family-names: "Wenig"
    given-names: "Philipp"
  - family-names: "Papenbrock"
    given-names: "Thorsten"

conference:
  name: "Conference Lernen, Wissen, Daten, Analysen"
  acronym: "LWDA"
  series: "LWDA '23"
  location: "Marburg, Germany"
  date-start: 2023-10-09
  date-end: 2023-10-11

repository-code: "https://github.com/floriansiepe/CAML"

doi: "TBD"

preferred-citation:
  type: "conference-paper"
  authors:
    - family-names: "Siepe"
      given-names: "Florian"
      orcid: "0009-0008-5911-5327"
    - family-names: "Wenig"
      given-names: "Phillip"
      orcid: "0000-0002-8942-4322"
    - family-names: "Papenbrock"
      given-names: "Thorsten"
      orcid: "0000-0002-4019-8221"
  title: "A Few Models to Rule Them All: Aggregating Machine Learning Models"
  conference:
    name: "Conference Lernen, Wissen, Daten, Analysen"
    acronym: "LWDA"
    series: "LWDA '23"
    location: "Marburg, Germany"
    date-start: 2023-10-09
    date-end: 2023-10-11
  year: 2023
  publisher:
    name: "CEUR Workshop Proceedings"
  url: "https://github.com/floriansiepe/CAML"
  numpages: 12

GitHub Events

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  • Issue comment event: 2
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  • Create event: 5
Last Year
  • Delete event: 3
  • Issue comment event: 2
  • Push event: 1
  • Pull request event: 9
  • Create event: 5

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Last synced: 6 months ago

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  • Total pull requests: 29
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  • Average time to close pull requests: 18 days
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  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.1
  • Merged pull requests: 24
  • Bot issues: 0
  • Bot pull requests: 29
Past Year
  • Issues: 0
  • Pull requests: 4
  • Average time to close issues: N/A
  • Average time to close pull requests: about 2 months
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  • Average comments per pull request: 0.25
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dependencies (50) python (1)

Dependencies

poetry.lock pypi
  • 211 dependencies
pyproject.toml pypi
  • black ^22.12.0
  • catboost ^1.1.1
  • darts ^0.24.0
  • deprecation ^2.1.0
  • fastcluster ^1.2.6
  • jupyter ^1.0.0
  • lightgbm ^3.3.3
  • optuna ^3.1.1
  • pandas ^2.0.3
  • pre-commit ^2.19.0
  • pyarrow ^10.0.1
  • python >=3.8,<3.11
  • scikit-learn ^1.3.0
  • seaborn ^0.12.1
  • torch ^2.0.1
  • torchaudio ^2.0.2
  • torchvision ^0.15.2
  • xgboost ^1.7.1