Issue | #Downvotes for this reason | By |
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TEST0aa73206aesklearn.linear_model._base.LinearRegression(1) | 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. |
TEST0aa73206aesklearn.linear_model._base.LinearRegression(1)_copy_X | true |
TEST0aa73206aesklearn.linear_model._base.LinearRegression(1)_fit_intercept | true |
TEST0aa73206aesklearn.linear_model._base.LinearRegression(1)_n_jobs | null |
TEST0aa73206aesklearn.linear_model._base.LinearRegression(1)_positive | false |
0.1486 ± 0.0063 |
0.1491 ± 0.0067 |
2178 |
0.9962 ± 0.0102 |
0.1894 ± 0.0107 |
0.189 ± 0.0103 |
0.9981 ± 0.0047 |