Table 2.

Results of artificial intelligence algorithm for POI prediction, by test group.

model_name	AUC	Accuracy	Precision	Recall	F1 score
LogisticRegression - Test	0.618	0.786	0.300	0.081	0.128
DecisionTreeClassifier - Test	0.624	0.807	0.500	0.135	0.213
GradientBoostingClassifier - Test	0.678	0.781	0.222	0.054	0.087
XGBClassifier - Test	0.638	0.807	0.500	0.108	0.178
LinearSVC - Test	0.633	0.802	0.400	0.054	0.095
knn - Test	0.552	0.776	0.286	0.108	0.157
adab - Test	0.575	0.771	0.360	0.243	0.290
LSTM - Test	0.571	0.781	0.222	0.054	0.087
CNNLSTM - Test	0.511	0.781	0.273	0.081	0.125
NeuralDecisionTree - Test	0.613	0.807	0.000	0.000	0.000

Notes: Logistic Regression, Decision Tree, Gradient Boosting, Linear SVC (Linear Support Vector Classification), XGB(Extreme gradient boosting)，Neural Decision Tree，knn (K-nearest neighbors), adab (AdaBoost), LSTM (Long Short - Term Memory), CNNLSTM (Convolutional Neural Network + Long Short - Term Memory).