Issue  #Downvotes for this reason  By 

sklearn.linear_model._base.LinearRegression(2)  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(2)_copy_X  true 
sklearn.linear_model._base.LinearRegression(2)_fit_intercept  true 
sklearn.linear_model._base.LinearRegression(2)_n_jobs  null 
sklearn.linear_model._base.LinearRegression(2)_normalize  false 
57.2447 ± 0.5326 Crossvalidation details (10 times 10fold Crossvalidation)

459180 Crossvalidation details (10 times 10fold Crossvalidation) 
68.4198 ± 0.5697 Crossvalidation details (10 times 10fold Crossvalidation)
