Research Article

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.

MethodsPrecisionRecallF1Accuracy

Random forest0.730.780.750.74
Gradient boosting classifier0.740.740.740.74
Naive Bayes0.760.710.730.74
Decision tree0.680.660.670.68
KNN0.690.650.670.68
Proposed method0.770.760.760.77