| Issue | #Downvotes for this reason | By |
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| copy_X | If True, X will be copied; else, it may be overwritten | default: true |
| fit_intercept | Whether to calculate the intercept for this model. If set to False, no intercept will be used in calculations (i.e. data is expected to be centered) | default: true |
| n_jobs | The number of jobs to use for the computation. This will only provide
speedup in case of sufficiently large problems, that is if firstly
`n_targets > 1` and secondly `X` is sparse or if `positive` is set
to `True`. ``None`` means 1 unless in a
:obj:`joblib.parallel_backend` context. ``-1`` means using all
processors. See :term:`Glossary | default: null |
| normalize | This parameter is ignored when ``fit_intercept`` is set to False If True, the regressors X will be normalized before regression by subtracting the mean and dividing by the l2-norm If you wish to standardize, please use :class:`~sklearn.preprocessing.StandardScaler` before calling ``fit`` on an estimator with ``normalize=False`` .. deprecated:: 1.0 `normalize` was deprecated in version 1.0 and will be removed in 1.2 | default: "deprecated" |
| positive | When set to ``True``, forces the coefficients to be positive. This option is only supported for dense arrays .. versionadded:: 0.24 | default: false |