… networks and support vector machines are applied. … uses concepts such as support vectors
and margins to find this hyperplane. A sequence of binary clusters was used to categorize …

… classification algorithms have been proposed. Support vector machine (SVM) as a powerful
classification algorithm has been achieved high classification accuracy and efficiency in …

… This study first evaluates the performance of a few machine learning models … Support
Vector Machine (GBSVM) which is constituted of gradient boosting and support vector machines. …

… “The Support Vector Machines totally founded on the idea of Decision points. … Support
Vector Machine algorithm is to create the line or decision boundary. The Support Vector Machine …

… This paper applied the firefly support vector machine in the supply chain financial … This
paper appliedthe firefly support vector machine in the supply chain financial evaluation for the first …

… Deep learning and support vector machine (SVM) technology are hot research topics in
the field of pattern recognition at present. Their combination can not only solve the problem …

… for service discovery. There are various algorithms in data mining such as support vector
machines, … The service discovered from the web services using mining algorithms obtained the …

… an approach for online review sentiment classification, which uses a conditional random field
… then weighted asymmetrically before a support vector machine classifier is used to obtain …

… , the supervised statistical learning algorithm, namely the Support Vector Machine (SVM)
was applied in this study to identify each land-use type to its highest accuracy. In recent years, …

… origin, where all the outliers are assumed to fall on the plane through the origin. This model
is known as one-class support vector machine (OCSVM). This algorithm returns a function g(x…