INNER CODE UNIT · Python

E

SalvatoreRa/tutorial · machine learning/scripts/MAR.py:176

            E = metrics.sum_energy_distances(pd.DataFrame(np.array(df.iloc[:, :-1])[train_index]), 
                           pd.DataFrame(X_train_imp), pd.DataFrame(df_mask))
            E= np.sum(E)
            print(E)
            FR = metrics.frechet_distance(pd.DataFrame(np.array(df.iloc[:, :-1])[train_index]), 
                           pd.DataFrame(X_train_imp), pd.DataFrame(df_mask))
            FR= np.sum(FR)
            print(FR)
            WA = metrics.dist_wasserstein(pd.DataFrame(np.array(df.iloc[:, :-1])[train_index]), 
                           pd.DataFrame(X_train_imp), pd.DataFrame(df_mask))
            WA= np.sum(WA)
            print(WA)

            m = [j, ms, perc, 'Mean', accuracy_score(y_test, y_test_pred), mae, 
                RMSR, KL, E, FR, WA, time.time() - algo_time]
            results.loc[len(results)] = m

            #### Imputing with the Median

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