A Classification Algorithm based on Concept Similarity

Author(s):  
João Paulo Domingos-Silva ◽  
Newton José Vieira
Author(s):  
Jing Peng ◽  
Dong-qing Yang ◽  
Chang-jie Tang ◽  
Jing Zhang ◽  
Jian-jun Hu

2012 ◽  
Vol 235 ◽  
pp. 9-14
Author(s):  
Chun Hua Ju ◽  
Li Li Mao

Data stream mining has been applied in many domains, but the concept drifts of data streams bring great obstacles to data mining. Current researches about classification algorithm for streaming data with concept drift have achieved many successes, while they pay little attention to the iterancy of data streams, namely, the situation of the historical concept reappears. For this characteristic, this paper puts forward that it utilizes the classifier model of the historical concepts or high similarity concepts through calculating the concept similarity to classify and predict. In this way, we don’t need training any more. Meanwhile, it reduces the cost of update model, speeds up the classification of the rate and improves the prediction efficiency.


Author(s):  
Jing Peng ◽  
Dong-qing Yang ◽  
Shi-Wei Tang ◽  
Jun Gao ◽  
Peng-yi Zhang ◽  
...  

2010 ◽  
Vol 33 (8) ◽  
pp. 1418-1426 ◽  
Author(s):  
Wei ZHENG ◽  
Chao-Kun WANG ◽  
Zhang LIU ◽  
Jian-Min WANG

2009 ◽  
Vol 29 (11) ◽  
pp. 3092-3095 ◽  
Author(s):  
Fang LI ◽  
Yi-yuan LI ◽  
Chong WANG

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