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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Deqiang Han ChongZhao Han Yi Yang |
| Copyright Year | 2007 |
| Description | Author affiliation: Xi 'an Jiaotong Univ., Xian (Deqiang Han; ChongZhao Han; Yi Yang) |
| Abstract | Multiple Classifiers Fusion is to utilize distinguished classifiers to resolve the same classification problem as a single classifier does, which can improve performance and generalization capability. In this paper, a new method of multiple classifiers fusion based on weighted evidence combination is proposed. Independent member classifiers are designed based on heterogeneous features by utilizing Artificial Neural Network (ANN). The Basic Probability Assignments (BPA or mass function) are generated based on member classifiers' outputs corresponding to a given test sample. The weights of each member classifier are defined based on their respective class-wise classification performance on training dataset. Based on weighted evidence combination, classification results of the fused classifier can be obtained, which is better than those derived based on Dempster rule of combination without weights. The experimental results provided in this paper verify the rationality and efficacy of the method proposed. |
| Starting Page | 2138 |
| Ending Page | 2143 |
| File Size | 221077 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424415311 |
| DOI | 10.1109/ICAL.2007.4338929 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Automation Heuristic algorithms Artificial neural networks Entropy Pattern recognition Artificial Neural Network (ANN) Evidence Theory Basic Probability Assignment Voting Multiple Classifiers Combination Fusion power generation Sampling methods Testing Logistics |
| Content Type | Text |
| Resource Type | Article |
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