comparison immuneml_train_ml_model.xml @ 7:45ca02982e1f draft

"planemo upload commit 8aef44a2b3bc8fc00a1efe0ce7ecab83eded053f-dirty"

6:2d3dd9ff7e84

      This tool can be used to run hyperparameter optimization over several different ML settings,
      which include ML models and their parameters, encodings and preprocessing steps. Nested cross-validation is used to identify the optimal combination of ML settings.

      This is a YAML-based Galaxy tool, if you prefer a button-based interface that assumes less ML knowledge,
      see `Train immune receptor classifiers (easy interface) <https://galaxy.immuneml.uio.no/root?tool_id=immuneml_train_classifiers>`_ and
      `Train immune repertoire classifiers (easy interface) <https://galaxy.immuneml.uio.no/root?tool_id=novice_immuneml_interface>`_.

      For more details on how to train ML models in Galaxy, see `the documentation <https://docs.immuneml.uio.no/latest/galaxy/galaxy_train_ml_models.html>`_.

      **Tool output**

7:45ca02982e1f

      This tool can be used to run hyperparameter optimization over several different ML settings,
      which include ML models and their parameters, encodings and preprocessing steps. Nested cross-validation is used to identify the optimal combination of ML settings.

      This is a YAML-based Galaxy tool, if you prefer a button-based interface that assumes less ML knowledge,
      see `Train immune receptor classifiers (easy interface) <root?tool_id=immuneml_train_classifiers>`_ and
      `Train immune repertoire classifiers (easy interface) <root?tool_id=novice_immuneml_interface>`_.

      For more details on how to train ML models in Galaxy, see `the documentation <https://docs.immuneml.uio.no/latest/galaxy/galaxy_train_ml_models.html>`_.

      **Tool output**