tailieunhanh - Profit agent classification using feature selection eigenvector centrality

In this paper we applied a feature selection based on graph method, graph method identifies the most important nodes that are interrelated with neighbors nodes. | Profit agent classification using feature selection eigenvector centrality International Journal of Mechanical Engineering and Technology IJMET Volume 10 Issue 3 March 2019 pp. 603 613 Article ID IJMET_10_03_062 Available online at http ijmet JType IJMET amp VType 10 amp IType 3 ISSN Print 0976-6340 and ISSN Online 0976-6359 IAEME Publication Scopus Indexed PROFIT AGENT CLASSIFICATION USING FEATURE SELECTION EIGENVECTOR CENTRALITY Zidni Nurrobi Agam Computer Science Department Bina Nusantara University Jakarta Indonesia 11480 Sani M. Isa Computer Science Department Bina Nusantara University Jakarta Indonesia 11480 Abstract Classification is a method that process related categories used to group data according to it are similarities. High dimensional data used in the classification process sometimes makes a classification process not optimize because there are huge amounts of otherwise meaningless data. in this paper we try to classify profit agent from and find the best feature that has a major impact to profit agent. Feature selection is one of the methods that can optimize the dataset for the classification process. in this paper we applied a feature selection based on graph method graph method identifies the most important nodes that are interrelated with neighbors nodes. Eigenvector centrality is a method that estimates the importance of features to its neighbors using Eigenvector centrality will ranking central nodes as candidate features that used for classification method and find the best feature for classifying Data Agent. Support Vector Machines SVM is a method that will be used whether the approach using Feature Selection with Eigenvalue Centrality will further optimize the accuracy of the classification. Keywords Classification Support Vector Machines Feature Selection Eigenvalue Centrality Graph-based. Cite this Article Zidni Nurrobi Agam and Sani M. Isa Profit Agent Classification Using Feature Selection Eigenvector .

• Kinh tế học
• Support Vector Machines
• High dimensional data
• Feature Selection with Eigenvalue Centrality
• Accuracy of the classification
• Data less good