Identification of X-Ray Fluorescent Spectral Paper Ashes Based on Support Vector Machine Algorithm

2021 ◽  
Vol 58 (3) ◽  
pp. 0330006-330006356
Author(s):  
李春宇 Li Chunyu ◽  
刘金坤 Liu Jinkun ◽  
姜红 Jiang Hong ◽  
徐乐乐 Xu Lele ◽  
满吉 Man Ji
2019 ◽  
Vol 15 (2) ◽  
pp. 275-280
Author(s):  
Agus Setiyono ◽  
Hilman F Pardede

It is now common for a cellphone to receive spam messages. Great number of received messages making it difficult for human to classify those messages to Spam or no Spam.  One way to overcome this problem is to use Data Mining for automatic classifications. In this paper, we investigate various data mining techniques, named Support Vector Machine, Multinomial Naïve Bayes and Decision Tree for automatic spam detection. Our experimental results show that Support Vector Machine algorithm is the best algorithm over three evaluated algorithms. Support Vector Machine achieves 98.33%, while Multinomial Naïve Bayes achieves 98.13% and Decision Tree is at 97.10 % accuracy.


Author(s):  
Mariana C. Potcoava ◽  
Gregory L. Futia ◽  
Emily A. Gibson ◽  
Isabel R. Schlaepfer

2015 ◽  
Vol 46 ◽  
pp. 205-213 ◽  
Author(s):  
Hossein Ziaee ◽  
Seyyed Mohsen Hosseini ◽  
Abdolmajid Sharafpoor ◽  
Mohammad Fazavi ◽  
Mohammad Mahdi Ghiasi ◽  
...  

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