A simple pattern classification method for alcohol-responsive proteins that are differentially expressed in mouse brain

PROTEOMICS ◽  
2004 ◽  
Vol 4 (11) ◽  
pp. 3369-3375 ◽  
Author(s):  
Bokyung Park ◽  
Seul-Ki Jeong ◽  
Won-Suk Lee ◽  
Je Kyung Seong ◽  
Young-Ki Paik
2011 ◽  
Vol 271-273 ◽  
pp. 911-916
Author(s):  
Xi Ai Yan ◽  
Jin Min Yang

The difficulty of filtrating network negative information lies in how to classify information correctly. As one of the classification method with the advantage of strong robustness and good understandability in the field of pattern classification, Naïve Bayes has been used widely. A method for filtrating network negative information on the basis of Naïve Bayes, improvement proposals aiming at the disadvantages of Naïve Bayes and amelioration of erroneous judgment of negative information by setting threshold value k have been put forward in this article. The experiment shows that by adjusting threshold value k can the integrity of the system can be optimum and can favorable application effects be achieved.


Author(s):  
Aiyesha Ma ◽  
Ishwar Sethi ◽  
Nilesh Patel

Community tagging offers valuable information for media search and retrieval, but new media items are at a disadvantage. Automated tagging may populate media items with few tags, thus enabling their inclusion into search results. In this paper, a multi-label decision tree is proposed and applied to the problem of automated tagging of media data. In addition to binary labels, the proposed Iterative Split Multi-label Decision Tree (IS-MLT) is easily extended to the problem of weighted labels (such as those depicted by tag clouds). Several datasets of differing media types show the effectiveness of the proposed method relative to other multi-label and single label classifier methods and demonstrate its scalability relative to single label approaches.Keywords: Automated Multimedia Tagging; Community Tagging; Multi-label Classification; Multi-label Decision Tree; Pattern Classification


2020 ◽  
Vol 9 (0) ◽  
pp. 10-20
Author(s):  
Masahiro Suzuki ◽  
Makoto Sasaki ◽  
Katsuhiro Kamata ◽  
Atsushi Nakayama ◽  
Isamu Shibamoto ◽  
...  

2009 ◽  
Vol 27 (5) ◽  
pp. 501-510 ◽  
Author(s):  
Uwe Ueberham ◽  
Peggy Lange ◽  
Elke Ueberham ◽  
Martina K. Brückner ◽  
Maike Hartlage‐Rübsamen ◽  
...  

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