An Efficient Guide Stars Classification Algorithm via Support Vector Machines

2009 ◽  
Author(s):  
Jing Sun ◽  
DeSheng Wen ◽  
GuangRui Li
Keyword(s):  
Support Vector Machines ◽  
Classification Algorithm ◽  
Support Vector ◽  
Vector Machines ◽  
Stars Classification

scholarly journals Cybercrime detection techniques based on support vector machines

2012 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Hanif - Mohaddes Deylami ◽  
Yashwant Prasad Singh
Keyword(s):  
Social Network ◽  
Support Vector Machines ◽  
Classification Accuracy ◽  
Classification Algorithm ◽  
Kernel Functions ◽  
Support Vector ◽  
Classification Algorithms ◽  
Detection Techniques ◽  
Detection Model ◽  
Vector Machines

This paper presents the cybercrime detection model by using support vector machines (SVMs) to classify social network (Facebook) dataset. We try to compare between three kinds of classification algorithms such as: SVMs, AdaBoostM1, and NaiveBayes in order to find a high percentage of classification accuracy. Finally, we conclude SVMs as the best classification algorithm, which uses different breeds of kernel functions in order to improve the classification accuracy on Facebook dataset. Besides, we are using the Weka 3.7.4 software to evaluate classifiers on Facebook dataset.

Sign in / Sign up

Export Citation Format

Share Document