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File /opt/anaconda3/lib/python3.12/site-packages/SparseSC/utils/match_space.py:135, in MTLassoCV_MatchSpace_factory.._MTLassoCV_MatchSpace_wrapper(X, Y, **kwargs)
134 def _MTLassoCV_MatchSpace_wrapper(X, Y, **kwargs):
--> 135 return _MTLassoCV_MatchSpace(
136 X, Y, v_pens=v_pens, n_v_cv=n_v_cv, sample_frac=sample_frac, Y_col_block_size=Y_col_block_size, se_factor=se_factor, normalize=normalize, fit_args=fit_args, **kwargs
137 )
File /opt/anaconda3/lib/python3.12/site-packages/SparseSC/utils/match_space.py:153, in _MTLassoCV_MatchSpace(X, Y, v_pens, n_v_cv, sample_frac, Y_col_block_size, se_factor, normalize, fit_args, **kwargs)
151 if Y_col_block_size is not None:
152 Y = block_summ_cols(Y, Y_col_block_size)
--> 153 varselectorfit = MultiTaskLassoCV(normalize=normalize, cv=n_v_cv, alphas=v_pens, **fit_args).fit(
154 X, Y
155 )
156 best_v_pen = varselectorfit.alpha
157 if se_factor is not None:
TypeError: MultiTaskLassoCV.init() got an unexpected keyword argument 'normalize'
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davidaristotle2012 commentedon Sep 7, 2025
Same here. This was deprecated since version 1.0. See scikit-learn docs. The suggestion from the documentation is
"""If you wish to standardize, please use StandardScaler before calling fit on an estimator with normalize=False."""