:orphan: .. only available via index, not via toctree .. title:: Package Recipe 'galaxy-ml' .. highlight: bash galaxy-ml ========= .. conda:recipe:: galaxy-ml :replaces_section_title: :noindex: APIs for Galaxy machine learning tools :homepage: https://github.com/goeckslab/Galaxy-ML :license: MIT :recipe: /`galaxy-ml `_/`meta.yaml `_ .. conda:package:: galaxy-ml |downloads_galaxy-ml| |docker_galaxy-ml| :versions: .. raw:: html
0.10.0-10.10.0-00.9.1-20.9.1-10.9.1-00.9.0-00.8.3-20.8.3-10.8.3-0 ``0.10.0-1``,  ``0.10.0-0``,  ``0.9.1-2``,  ``0.9.1-1``,  ``0.9.1-0``,  ``0.9.0-0``,  ``0.8.3-2``,  ``0.8.3-1``,  ``0.8.3-0``,  ``0.8.2-5``,  ``0.8.2-4``,  ``0.8.2-3``,  ``0.8.2-2``,  ``0.8.2-1``,  ``0.8.2-0``,  ``0.8.1-0``,  ``0.8.0-0``,  ``0.7.12-0``,  ``0.7.11-0``,  ``0.7.10-1``,  ``0.7.10-0``,  ``0.7.9-0``,  ``0.7.8-0``,  ``0.7.7-1``,  ``0.7.7-0``,  ``0.7.5-0``,  ``0.7.4.1-0`` .. raw:: html
:depends asteval: ``>=0.9.14`` :depends bleach: ``>=3.3.0`` :depends graphviz: ``>=2.40.1`` :depends h5py: ``>=3.6,<3.8`` :depends htslib: :depends imbalanced-learn: ``>=0.9,<0.10`` :depends joblib: ``>=1.0`` :depends keras: ``>=2.10,<2.11`` :depends libgcc-ng: ``>=12`` :depends libstdcxx-ng: ``>=12`` :depends matplotlib-base: ``>=3.1.1`` :depends mlxtend: ``>=0.21,<0.22`` :depends numpy: ``>=1.22,<1.23`` :depends numpy: ``>=1.22.4,<2.0a0`` :depends pandas: ``>=1.0,<1.3`` :depends plotly: ``>=4.10.0,<5.0`` :depends pydot: ``>=1.4`` :depends pyfaidx: :depends pytabix: :depends python: ``>=3.9,<3.10.0a0`` :depends python_abi: ``3.9.* *_cp39`` :depends scikit-learn: ``>=1.1,<1.2`` :depends scikit-optimize: ``>=0.9`` :depends scipy: ``>=1.3.1`` :depends six: ``<=1.15.0`` :depends skrebate: ``>=0.60,<0.70`` :depends tabix: :depends tensorflow: ``>=2.10,<2.11`` :depends xgboost: ``>=1.6,<1.8`` :requirements: .. rubric:: Installation You need a conda-compatible package manager (currently either `micromamba `_, `mamba `_, or `conda `_) and the Bioconda channel already activated (see :ref:`set-up-channels`). While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see `here `_ for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others. Given that you already have a conda environment in which you want to have this package, install with:: mamba install galaxy-ml and update with:: mamba update galaxy-ml To create a new environment, run:: mamba create --name myenvname galaxy-ml with ``myenvname`` being a reasonable name for the environment (see e.g. the `mamba docs `_ for details and further options). Alternatively, use the docker container:: docker pull quay.io/biocontainers/galaxy-ml: (see `galaxy-ml/tags`_ for valid values for ````) .. |downloads_galaxy-ml| image:: https://img.shields.io/conda/dn/bioconda/galaxy-ml.svg?style=flat :target: https://anaconda.org/bioconda/galaxy-ml :alt: (downloads) .. |docker_galaxy-ml| image:: https://quay.io/repository/biocontainers/galaxy-ml/status :target: https://quay.io/repository/biocontainers/galaxy-ml .. _`galaxy-ml/tags`: https://quay.io/repository/biocontainers/galaxy-ml?tab=tags .. raw:: html Download stats ----------------- .. raw:: html :file: ../../templates/package_dashboard.html Link to this page ----------------- Render an |install-with-bioconda| badge with the following MarkDown:: [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/galaxy-ml/README.html) .. |install-with-bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/galaxy-ml/README.html