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TESTcd867110c9sklearn.linear_model._base.LinearRegression

Visibility: public Uploaded 25-11-2022 by Continuous Integration
sklearn==0.24.0
numpy>=1.13.3
scipy>=0.19.1
joblib>=0.11
threadpoolctl>=2.0.0 1 runs

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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 for n_targets > 1 and sufficient large problems
``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`` | default: false |

positive | When set to ``True``, forces the coefficients to be positive. This option is only supported for dense arrays .. versionadded:: 0.24 | default: false |

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