5 examples of 'sklearn linear regression get coefficients' in Python

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53def coefficient_for_category(predictors, category):
54 predictor = [p for p in predictors if p.get('value') == category]
55
56 if not predictor:
57 return 0
58
59 return float(predictor[0].get('coefficient'))
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84def _calculate_coefficients(self):
85 return self._coefficients
138@property
139def coef_(self):
140 return self.clf_.coef_
1017@property
1018def coef_(self):
1019 """
1020 Get the model's coefficients on the covariates.
1021
1022 Returns
1023 -------
1024 coef_ : {(d,), (p, d)} nd array like
1025 The coefficients of the variables in the linear regression. If label y
1026 was p-dimensional, then the result is a matrix of coefficents, whose p-th
1027 row containts the coefficients corresponding to the p-th coordinate of the label.
1028 """
1029 if self.fit_intercept:
1030 if self._n_out == 0:
1031 return self._param[1:]
1032 else:
1033 return self._param[1:].T
1034 else:
1035 if self._n_out == 0:
1036 return self._param
1037 else:
1038 return self._param.T
87def calc_linear_regression(coeff, x):
88 result = 0
89 for i in range(1, len(coeff)):
90 result += x[i - 1] * coeff[i]
91
92 result += coeff[0]
93 return result

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