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sklearn.linear_model.base.LinearRegression

sklearn.linear_model.base.LinearRegression

Visibility: public Uploaded 18-12-2019 by George Volkov sklearn==0.21.2 numpy>=1.6.1 scipy>=0.9 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0.21.2
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Ordinary least squares Linear Regression.

Parameters

copy_XIf True, X will be copied; else, it may be overwrittendefault: true
fit_interceptwhether to calculate the intercept for this model. If set to False, no intercept will be used in calculations (e.g. data is expected to be already centered)default: true
n_jobsThe 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 ` for more details.default: null
normalizeThis 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

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