iter_sklearn_dataset¶
Iterates rows from one of the datasets provided by scikit-learn.
This allows you to use any dataset from scikit-learn's datasets
module. For instance, you can use the fetch_openml
function to get access to all of the datasets from the OpenML website.
Parameters¶
-
dataset ('sklearn.utils.Bunch')
A scikit-learn dataset.
-
kwargs
Extra keyword arguments are passed to the underlying call to
stream.iter_array
.
Examples¶
>>> import pprint
>>> from sklearn import datasets
>>> from river import stream
>>> dataset = datasets.load_diabetes()
>>> for xi, yi in stream.iter_sklearn_dataset(dataset):
... pprint.pprint(xi)
... print(yi)
... break
{'age': 0.0380759064334241,
'bmi': 0.0616962065186885,
'bp': 0.0218723549949558,
's1': -0.0442234984244464,
's2': -0.0348207628376986,
's3': -0.0434008456520269,
's4': -0.00259226199818282,
's5': 0.0199084208763183,
's6': -0.0176461251598052,
'sex': 0.0506801187398187}
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