Analysis of the Customer Churn Prediction Project in the Hotel Industry Based on Text Mining and the Random Forest Algorithm

Table 4

Performance comparison of random forest, gradient boosting classifier, naive Bayes, decision tree, KNN methods, and the proposed system.

Methods	Precision	Recall	F1	Accuracy
Random forest	0.73	0.78	0.75	0.74
Gradient boosting classifier	0.74	0.74	0.74	0.74
Naive Bayes	0.76	0.71	0.73	0.74
Decision tree	0.68	0.66	0.67	0.68
KNN	0.69	0.65	0.67	0.68
Proposed method	0.77	0.76	0.76	0.77