| Issue | #Downvotes for this reason | By |
|---|
| sklearn.linear_model._base.LinearRegression(3) | Ordinary least squares Linear Regression. LinearRegression fits a linear model with coefficients w = (w1, ..., wp) to minimize the residual sum of squares between the observed targets in the dataset, and the targets predicted by the linear approximation. |
| sklearn.linear_model._base.LinearRegression(3)_copy_X | true |
| sklearn.linear_model._base.LinearRegression(3)_fit_intercept | true |
| sklearn.linear_model._base.LinearRegression(3)_n_jobs | null |
| sklearn.linear_model._base.LinearRegression(3)_normalize | "deprecated" |
| sklearn.linear_model._base.LinearRegression(3)_positive | false |
0.0087 ± 0.0008 Cross-validation details (10-fold Crossvalidation)
|
1000 Cross-validation details (10-fold Crossvalidation) |
0.012 ± 0.0011 Cross-validation details (10-fold Crossvalidation)
|