… different algorithms that Support Vector Machine outperforms other … of feature selection
technique while Naïve Bayes and J48 show slight improvement on the use of feature selection in …

… Step 2: Factor selection We next used the ORAE feature selection technique to select the
most important factors for landslide occurrence in the study area (Section 4.7). …

… and the best results were obtained by 1-NN and Naïve Bayes… The results show that (J48)
decision tree classifier has the … Secondly, we performed the attribute selection process to …

… SVM [26] uses a Support Vector Machine to estimate feature importance. … classification
techniques (ie, NB, J48, and OneR). They conclude that Naïve Bayes yields the best classification …

… approaches such as Support Vector Machine (SVM) [16] and … Bayes algorithm and was more
scalable than Support Vector … to select the k best features using one of the feature selection …

… with other classifiers like Support Vector Machines (SVM) [13], Naive Bayesian classifier (NB)
[… 3 it can be inferred that compared to other classifiers, CVM and Naïve Bayesian classifiers …

… for classification using Naïve Bayes (NB), Support Vector … The Naïve Bayes (NB) and
J48(C4.5) techniques are … used are Naïve Bayes, Support Vector Machine and Decision …

… Then, we combine these methods with the support vector machine (SVM) classifier to find the
best … and give an overview of feature selection and some basic concepts on support vector …

… , we use six different machine learning algorithms (ie J48, Random Forest, One R, Decision
Tree, Bayes Net and Naïve Bayes) to classify … worm activity via support vector machines and …

… and Smooth Support Vector Machine (SSVM) classification to … of the selected attribute which
are performing in Naïve Bayes … We use J48 algorithm here. This algorithm is dependent on …