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Minor Documentation Fixes: TaskID for Example Custom Flow; Comment on Homepage; More documentation for components #1243

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merged 8 commits into from
Apr 18, 2023
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Minor Documentation Fixes: TaskID for Example Custom Flow; Comment on Homepage; More documentation for components #1243

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ca58461
fix task ID for Iris task
LennartPurucker Apr 15, 2023
8c57c4d
update comment on homepage
LennartPurucker Apr 15, 2023
524c01c
added additional documentation specific to the `components` parameter.
LennartPurucker Apr 16, 2023
da53346
add change to progress.rst
LennartPurucker Apr 17, 2023
ab72f5b
Fix dataframe append being deprecated by replacing it with (backwards…
LennartPurucker Apr 18, 2023
478b65e
fix logging example and add new changes to progress.rst
LennartPurucker Apr 18, 2023
0a53e74
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Apr 18, 2023
da9f1b1
fix comment too long
LennartPurucker Apr 18, 2023
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2 changes: 1 addition & 1 deletion doc/index.rst
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Expand Up @@ -30,7 +30,7 @@ Example
('estimator', tree.DecisionTreeClassifier())
]
)
# Download the OpenML task for the german credit card dataset with 10-fold
# 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.
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6 changes: 5 additions & 1 deletion examples/30_extended/custom_flow_.py
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Expand Up @@ -77,6 +77,8 @@
# you can use the Random Forest Classifier flow as a *subflow*. It allows for
# all hyperparameters of the Random Classifier Flow to also be specified in your pipeline flow.
#
# Note: you can currently only specific one subflow as part of the components.
#
# In this example, the auto-sklearn flow is a subflow: the auto-sklearn flow is entirely executed as part of this flow.
# This allows people to specify auto-sklearn hyperparameters used in this flow.
# In general, using a subflow is not required.
Expand All @@ -87,6 +89,8 @@
autosklearn_flow = openml.flows.get_flow(9313) # auto-sklearn 0.5.1
subflow = dict(
components=OrderedDict(automl_tool=autosklearn_flow),
# If you do not want to reference a subflow, you can use the following:
# components=OrderedDict(),
)

####################################################################################################
Expand Down Expand Up @@ -124,7 +128,7 @@
OrderedDict([("oml:name", "time"), ("oml:value", 120), ("oml:component", flow_id)]),
]

task_id = 1965 # Iris Task
task_id = 1200 # Iris Task
task = openml.tasks.get_task(task_id)
dataset_id = task.get_dataset().dataset_id

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