Table 5 Performance of shallow ML classifiers with feature selection (results in %age).
From: Using deep learning and word embeddings for predicting human agreeableness behavior
Features | Models | Accuracy | Precision | Recall | F1-Score |
|---|---|---|---|---|---|
TF-IDF | KNN | 70 | 71 | 70 | 69 |
NB | 75 | 78 | 75 | 74 | |
LR | 84 | 84 | 84 | 84 | |
DT | 84 | 84 | 84 | 84 | |
SVM | 84 | 84 | 84 | 84 | |
GB | 82 | 82 | 82 | 82 | |
RF | 79 | 79 | 79 | 79 | |
XGB | 83 | 83 | 83 | 83 | |
AdaBoost | 81 | 81 | 81 | 81 | |
POS | KNN | 57 | 57 | 57 | 57 |
NB | 58 | 57 | 57 | 58 | |
LR | 62 | 62 | 62 | 61 | |
DT | 54 | 54 | 54 | 54 | |
SVM | 68 | 68 | 68 | 68 | |
GB | 62 | 62 | 62 | 62 | |
RF | 61 | 60 | 61 | 60 | |
XGB | 58 | 57 | 58 | 57 | |
AdaBoost | 61 | 61 | 61 | 61 |
