Predicting the gender of Indonesian names
Table 2: Results from basic and n-gram features
['Features', 'Accuracy (%) NB', 'Accuracy (%) LogReg', 'Accuracy (%) XGBoost', '[ITALIC] F1 (%) NB', '[ITALIC] F1 (%) LogReg', '[ITALIC] F1 (%) XGBoost']
We can see that we achieved the best performance for Naïve Bayes and logistic regression using 3-gram features, while using 2-gram shows a slightly better result for XGBoost.