Linear Regression¶
Ordinary linear regression
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Outputs:
model: model
Model
Configuration:
- fit_intercept
- whether 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).
- 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 usesklearn.preprocessing.StandardScaler
before callingfit
on an estimator withnormalize=False
.- n_jobs
- The number of jobs to use for the computation. If -1 all CPUs are used. This will only provide speedup for n_targets > 1 and sufficient large problems.
Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.