Table 4 Accuracy of the resulting dataset after having applied of the feature selection methods using the SVM, Boosting (Adaboost) and Naive Bayes classifiers
| Â | Accuracy | Precision | Recall | F1score |
|---|---|---|---|---|
SVM | Â | Â | Â | Â |
Gradient Tree Boosting | 98% | 100% | 94% | 96% |
L1-based | 88% | 86% | 85% | 84% |
Random Forest | 91% | 91% | 85% | 87% |
Univariate | 78% | 80% | 78% | 78% |
Boosting (Adaboost) | Â | Â | Â | Â |
Gradient Tree Boosting | 94% | 100% | 92% | 9% |
L1-based | 91% | 91% | 91% | 89% |
Random Forest | 95% | 100% | 94% | 96% |
Univariate | 87% | 87% | 87% | 85% |
NaiveBayes | Â | Â | Â | Â |
Gradient Tree Boosting | 98% | 96% | 100% | 98% |
L1-based | 61% | 60% | 78% | 67% |
Random Forest | 92% | 86% | 98% | 91% |
Univariate | 60% | 53% | 87% | 66% |