… , while the Support Vector Machine (Sigmoid) has an accuracy of 70%, without feature
selection the C5. 0 algorithm has an accuracy of 66%, Support Vector Machine between RBF and …

… Bayes. The NSL-KDD dataset was experimented with and the … support vector machine (SVM),
Naive Bayes and J48. Their findings showed that identifying essential features and using …

… by the hyperplane or support vector machine. Some of the … The different classification
algorithms J48, JRIP, Naïve Bayes… random forest, naïve Bayes of complete and reduced features …

… feature selection methods to the classification performances using support vector machines.
… They classify UNSW-NB15 features using J48 and naïve bayes algorithms. They obtain the …

… algorithms, namely J48 (Tree-based), Decision Table (Rule-based), and Naïve … feature
selection, data splitting, text vectorization or feature extraction, and classification using a machine …

… Based on the analysis and comparison of multiple algorithms, Random … J48 based on the
10-fold cross-validation method. Implementing J48 and J48 + GA improved the classification …

… , by using the naive Bayes classifier. … features of the support vector machine. It was noted
that the particle swarm optimization support vector machine model effectively tunes the support …

… They used selected variables as input for model training of several classification algorithms
such as Random Forest, J48, and GLM. As a result, the prediction accuracy increases in …

… feature elimination (RFE) (A-GA-RFE) feature selection … , such as Random Forest, J48, SMO,
Naïve Bayes, among others [5]. In … methods using Random Forest, SVM and Naive Bayes …

… uses Naïve Bayes, J48 to increase the classification … classification accuracy within a reduced
set of features, we have included a wrapper based GPSOGSA with Support Vector Machine …