AutoML-Python-Benchmark

Benchmarks of AutoML Frameworks for time series forecasting, anomaly detection and classification.

Primary Python version: 3.10.14

Table of Contents

1. Publications
2. Datasets
3. CUDA
4. Installation
5. Experiments
6. Development
7. Contact
8. Citation

Publications

A Comparative Analysis of Automated Machine Learning Libraries for Electricity Price Forecasting (2024)

• Tag
• Code
• These experiments are run with Python 3.9 and CUDA versions 11.2 and 11.7.

Installation

Removed. To be redrafted.

CUDA

To run this code, you will need to install CUDA for TensorFlow and PyTorch.

• CUDA compatibilities for TensorFlow are listed here.
• CUDA compatibilities for PyTorch are listed here

To be redrafted.

Datasets

Removed. To be redrafted.

Before running the code, datasets and repositories must be downloaded

Experiments

Removed. To be redrafted.

Development

Removed. To be redrafted.

SonarQube

This requires Docker.

Allow Docker containers to access GPUs:

# Required to install nvidia packages
wget https://nvidia.github.io/nvidia-docker/gpgkey --no-check-certificate
sudo apt-key add gpgkey
sudo apt-get update

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install -y nvidia-docker2

# Install nvidia package
sudo apt-get install nvidia-container-runtime nvidia-container-toolkit

Set up SonarQube server via docker-compose:

# Start server
docker-compose up --timeout 300 -d --build --force-recreate

# Download repositories
sh -i ./shell/repo_clone_or_pull.sh

# Run sonar-scanner
sh -i ./shell/repo_sonar_scanner.sh

# Stop server:
docker-compose down

Contact

Please feel free to get in touch at [email protected]

Citation

Christian O'Leary (2024) AutoML Python Benchmark.

@software{AutoML-Python-Benchmark,
author = {Christian O'Leary},
title = {AutoML Python Benchmark},
doi = {10.5281/zenodo.13133203},
howpublished = {\url{https://github.com/christian-oleary/AutoML-Python-Benchmark}},
year = {2024}
}