On multiclass text classification algorithm based on 1-a-r and multiconlitron
| Autor: | Yuping Qin, Aihua Zhang, Fengfeng Qin, Qiangkui Leng |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry Binary number Pattern recognition Machine learning computer.software_genre Class (biology) Multiclass classification Support vector machine Statistical classification Categorization Kernel (statistics) Algorithm design Artificial intelligence business Algorithm computer |
| Zdroj: | 2017 6th Data Driven Control and Learning Systems (DDCLS). |
| DOI: | 10.1109/ddcls.2017.8068099 |
| Popis: | Aim to multiclass text categorization problem, a classification algorithm based on multiconlitron and 1-a-r method is presented. 1-a-r method is used to convert a multiclass categorization problem to several binary problems. Multiconlitron is constructed for each binary problem in input space. For the text to be classified, its class is decided by multiconlitrons. The classification experiments are made on the Reuters 21578. Experimental results indicate that the proposed algorithm has better classification performance compare with 1-a-r SVMs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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