simple_flows_and_runs_tutorial.py

"""
Flows and Runs
==============

A simple tutorial on how to train/run a model and how to upload the results.
"""

# License: BSD 3-Clause

from sklearn import ensemble, neighbors

import openml

############################################################################
# .. warning::
#    .. include:: ../../test_server_usage_warning.txt
openml.config.start_using_configuration_for_example()

############################################################################
# Train a machine learning model
# ==============================

# NOTE: We are using dataset "diabetes" from the test server: https://test.openml.org/d/20
dataset = openml.datasets.get_dataset(dataset_id="diabetes", version=1)
X, y, categorical_indicator, attribute_names = dataset.get_data(
    target_names=dataset.default_target_attribute
)
clf = neighbors.KNeighborsClassifier(n_neighbors=3)
clf.fit(X, y)

############################################################################
# Running a model on a task
# =========================

task = openml.tasks.get_task(119)
clf = ensemble.RandomForestClassifier()
run = openml.runs.run_model_on_task(clf, task)
print(run)

############################################################################
# Publishing the run
# ==================

myrun = run.publish()
print(f"Run was uploaded to {myrun.openml_url}")
print(f"The flow can be found at {myrun.flow.openml_url}")

############################################################################
openml.config.stop_using_configuration_for_example()