5 examples of 'sklearn linear regression get coefficients' in Python
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53 def 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'))
84 def _calculate_coefficients(self): 85 return self._coefficients
138 @property 139 def coef_(self): 140 return self.clf_.coef_
1017 @property 1018 def 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
87 def 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