OpenMLCollaborative Machine Learning in PythonWelcome to the documentation of the OpenML Python API, a connector to the collaborative machine learning platform OpenML.org. The OpenML Python package allows to use datasets and tasks from OpenML together with scikit-learn and share the results online.Exampleimport openml
from sklearn import impute, tree, pipeline
# Define a scikit-learn classifier or pipeline
clf = pipeline.Pipeline(
steps=[
('imputer', impute.SimpleImputer()),
('estimator', tree.DecisionTreeClassifier())
]
)
# Download the OpenML task for the pendigits dataset with 10-fold
# cross-validation.
task = openml.tasks.get_task(32)
# Run the scikit-learn model on the task.
run = openml.runs.run_model_on_task(clf, task)
# Publish the experiment on OpenML (optional, requires an API key.
# You can get your own API key by signing up to OpenML.org)
run.publish()
print(f'View the run online: {run.openml_url}')
You can find more examples in our Examples Gallery.How to get OpenML for pythonYou can install the OpenML package via pip:pip install openml
For more advanced installation information, please see the Installation & Set up section.Content
Further information
