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

Before Change

        else:
            self.inverse_covariance = inverse_covariance
        // estimate of the parameters
        self.beta_estimate = np.dot(np.dot(self.inverse_covariance, X_ones.T), y)        
        // now we need the estimate of the noise variance
        // reference: https://stat.ethz.ch/R-manual/R-devel/library/stats/html/summary.lm.html
        residuals_sqr = (y - self.predict(X)) ** 2

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