9439f5215fde61ee40910b0320ff4dd8d28571e2,fancyimpute/bayesian_ridge_regression.py,BayesianRidgeRegression,fit,#BayesianRidgeRegression#Any#Any#Any#,28

Before Change

                lambda_reg = self.lambda_reg
            regularization_matrix = lambda_reg * np.eye(d)
            regularization_matrix[-1, -1] = 0  // don"t need to regularize the intercept
            self.inverse_covariance = np.linalg.inv(
               outer_product + regularization_matrix)
        else:
            self.inverse_covariance = inverse_covariance
        // estimate of the parameters
        self.beta_estimate = np.dot(np.dot(self.inverse_covariance, X_ones.T), y)        

After Change

            else:
                lambda_reg = self.lambda_reg

            for i in range(d - 1):
                // Replacing `outer_product + lambda_reg * eye(d)` with
                // a direct modification of the outer_product matrix
                //
                // We"re trading a little more time spent in the Python
                // interpreter with a savings of allocated arrays.
                outer_product[i, i] += lambda_reg

            self.inverse_covariance = inv(outer_product)
        else:
            self.inverse_covariance = inverse_covariance
        // estimate of the parameters

Instances