Linear Regression

../../../../_images/linear_regression.svg

Ordinary linear regression

Documentation

Attributes

coef_

Estimated coefficients for the linear regression problem. If multiple targets are passed during the fit (y 2D), this is a 2D array of shape (n_targets, n_features), while if only one target is passed, this is a 1D array of length n_features.

intercept_

Independent term in the linear model. Set to 0.0 if fit_intercept = False.

residues_

Definition

Output ports

model model

Model

Configuration

Fit intercept (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).

Number of jobs (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 joblib.parallel_backend context. -1 means using all processors. See n_jobs for more details.

Implementation

class node_regression.LinearRegression[source]