Bayesian Nonparametric Multi-Label Clustering
碩士 === 國立交通大學 === 資訊科學與工程研究所 === 103 === Multi-label learning problem has attracted a lot of attention in recent years, but most of the algorithms focus on classification problem. This paper proposes the first method to solve multi-label clustering problem. Based on the multi-label clustering concep...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/83405556752845648524 |
| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 103 === Multi-label learning problem has attracted a lot of attention in recent years, but most of the algorithms focus on classification problem. This paper proposes the first method to solve multi-label clustering problem. Based on the multi-label clustering concept, this paper uses Bayesian nonparametric model to predict the multi-label data sets. The advantage of the model is to let the model grow by itself. Another contribution of this paper is to create a new evaluation method for multi-label clustering problem. Because the existing multi-label classification methods assume the number of classes is fixed, so the evaluation methods use in classification problem is not suitable in clustering result. And the experiments show that the proposed method can perform better than other methods.
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