Complexity / 2020 / Article / Tab 3

Research Article

Fake News Detection Using Machine Learning Ensemble Methods

Table 3

Precision on the 4 datasets.

DS1DS2DS3DS4

Logistic regression (LR)0.980.920.930.88
Linear SVM (LSVM)0.980.310.540.88
Multilayer perceptron0.970.320.930.92
K-nearest neighbors (KNN)0.910.220.850.8

Ensemble learners
Random forest (RF)0.990.30.980.92
Voting classifier (RF, LR, KNN)0.960.880.920.86
Voting classifier (LR, LSVM, CART)0.940.860.880.83
Bagging classifier (decision trees)0.980.940.930.9
Boosting classifier (AdaBoost)0.980.920.920.86
Boosting classifier (XGBoost)0.990.940.960.92

Benchmark algorithms
Perez-LSVM0.990.790.960.9
Wang-CNN0.840.650.480.72
Wang-Bi-LSTM0.920.430.50.65

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