计算机科学 ›› 2012, Vol. 39 ›› Issue (11): 204-207.
• 人工智能 • 上一篇 下一篇
李岩波.宋琼,郭新辰
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摘要: 将流形距离作为样本间相似性的基本度量测度,加入成对约束信息,通过近部传播得出新的度量矩阵。把聚 类问题转化为一优化数学模型。采用克隆选择算法求解这个优化模型,得出最后的聚类结果,通过人工数据集和UCI 标准数据集验证了这种方法具有较高的准确性。
关键词: 流形距离,半监督聚类,人工免疫算法
Abstract: Manifold distance was used as the basic measure of the sample similarity between samples. The pair-wise constrains prior information was introduced,then the measure matrix was obtained through affinity propagation. So the clustering problem was transformed as one optimal model. Clonal selection algorithm was employed to solve this model, and the clustering results were given. Experiments on artificial data sets and UCI benchmark data set show that the pro- posed method can give the better accuracy.
Key words: Manifold distance, Semi supervised clustering, Artificial immune algorithm
李岩波.宋琼,郭新辰. 基于流形距离的人工免疫半监督聚类算法[J]. 计算机科学, 2012, 39(11): 204-207. https://doi.org/
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