Online neural network model for non-stationary and imbalanced data stream classification

2013 ◽  
Vol 5 (1) ◽  
pp. 51-62 ◽  
Author(s):  
Adel Ghazikhani ◽  
Reza Monsefi ◽  
Hadi Sadoghi Yazdi
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Data Stream ◽  
Imbalanced Data ◽  
Stream Classification ◽  
Data Stream Classification

The Research of Data Stream Classification Based on Rough Set Theory-Neural Network Integration

2013 ◽  
Vol 441 ◽  
pp. 717-720
Author(s):  
Zhi Bo Ren ◽  
Chun Miao Yan ◽  
Yu Zhou Wei ◽  
Lei Sun
Keyword(s):  
Neural Network ◽  
Set Theory ◽  
Rough Set ◽  
Data Stream ◽  
High Speed ◽  
Rough Set Theory ◽  
Classification Model ◽  
Stream Classification ◽  
Data Stream Classification ◽  
Voting Rule

According to the high speed of data arriving, a large amount of data and concept drifting in the stream model, combining the techniques of rough set theory, neural network and voting rule, we put forward a new data stream classification model, which is a multi-classifier integration based on rough set theory, neural network. Firstly, it reduces all attributes using rough set theory; secondly, it constructs base classifiers on the data chunks after the reduction of attributes using the improved BP neural network; finally, it fuses various base classifiers into an ensemble by voting rule. Through applying the model to classify data stream, the experiment results show that the ensemble method is feasible and effective.

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