jakobzeitler/FR-OptApp

OptCore OptApp using BoTorch and SingleTaskGP

A proof-of-concept pipeline for performing hyperparameter optimization of machine learning models with Nextflow.

Requirements

• Unix-like operating system (Linux, macOS, etc)
• Java >=11
• Conda or Docker

Quickstart

1. Install Nextflow (version 22.10.x or higher):

   curl -s https://get.nextflow.io | bash

2. Launch the pipeline:

   # use conda natively (requires Conda)
   ./nextflow run nextflow-io/hyperopt -profile conda
   
   # use Wave containers (requires Docker)
   ./nextflow run nextflow-io/hyperopt -profile wave

3. When the pipeline completes, you can view the training and prediction results in the results folder.

Note: the first time you execute the pipeline, Nextflow will take a few minutes to download the pipeline code from this GitHub repository and any related software dependencies (e.g. conda packages or Docker images).

The hyperopt pipeline uses Python (>=3.10) and several Python packages for machine learning and data science. These dependencies are defined in the conda.yml file.