4ca74616a886c24dd7946e00f535f323e2e13787,astroML/linear_model/linear_regression.py,LinearRegression,fit,#LinearRegression#Any#Any#Any#,38
Before Change
return X
def fit(self, X, y, dy=1):
self.y_ = np.asarray(y)
self.X_ = np.asarray(X)
self.dy_ = dy
X_fit, y_fit = self._process_Xy(self.X_, self.y_, dy)
self.coef_ = np.linalg.solve(np.dot(X_fit.T, X_fit),
np.dot(X_fit.T, y_fit))
return self
After Change
return model
def fit(self, X, y, y_error=1):
kwds = {}
if self.kwds is not None:
kwds.update(self.kwds)
kwds["fit_intercept"] = False
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 4
Instances
Project Name: astroML/astroML
Commit Name: 4ca74616a886c24dd7946e00f535f323e2e13787
Time: 2014-10-22
Author: jakevdp@gmail.com
File Name: astroML/linear_model/linear_regression.py
Class Name: LinearRegression
Method Name: fit
Project Name: freelunchtheorem/Conditional_Density_Estimation
Commit Name: 8d4958cf59ef5d0372e495a310908eced205a009
Time: 2019-01-22
Author: jonas.rothfuss@gmx.de
File Name: cde/density_estimator/LSCDE.py
Class Name: LSConditionalDensityEstimation
Method Name: _param_grid
Project Name: NifTK/NiftyNet
Commit Name: ebbc9fc0fc52a650ebd5bbbd954733bada35672e
Time: 2017-08-08
Author: wenqi.li@ucl.ac.uk
File Name: niftynet/layer/histogram_normalisation.py
Class Name: HistogramNormalisationLayer
Method Name: layer_op