/opt/hostedtoolcache/Python/3.8.14/x64/lib/python3.8/site-packages/sklearn/linear_model/_base.py:133: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:
from sklearn.pipeline import make_pipeline
model = make_pipeline(StandardScaler(with_mean=False), LassoLars())
If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:
kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)
Set parameter alpha to: original_alpha * np.sqrt(n_samples).
warnings.warn(
