SKL2RiverRegressor

Compatibility layer from scikit-learn to River for regression.

Parameters

• estimator ('sklearn_base.BaseEstimator')

  A scikit-learn transformer which has a partial_fit method.

Examples

>>> from river import compat
>>> from river import evaluate
>>> from river import metrics
>>> from river import preprocessing
>>> from river import stream
>>> from sklearn import linear_model
>>> from sklearn import datasets

>>> dataset = stream.iter_sklearn_dataset(
...     dataset=datasets.load_diabetes(),
...     shuffle=True,
...     seed=42
... )

>>> scaler = preprocessing.StandardScaler()
>>> sgd_reg = compat.convert_sklearn_to_river(linear_model.SGDRegressor())
>>> model = scaler | sgd_reg

>>> metric = metrics.MAE()

>>> evaluate.progressive_val_score(dataset, model, metric)
MAE: 84.519485

Methods

learn_many

learn_one

Fits to a set of features x and a real-valued target y.

Parameters

• x
• y

Returns

self

predict_many

predict_one

Predict the output of features x.

Parameters

• x

Returns

The prediction.