INNER CODE UNIT · Python

WA

SalvatoreRa/tutorial · machine learning/scripts/MAR.py:186

            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
            # we are using here just the median, the principle is the same for the mean
            # we are using the median because is common method
            print('Imputation with Median')
            imp = SimpleImputer(missing_values=np.nan, strategy='median')
            imp.fit(X_train)
            X_train_imp =imp.transform(X_train)
            X_test_imp =imp.transform(X_test)

            clf = xgb.XGBClassifier(random_state=42)
            clf.fit(X_train_imp, y_train)

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