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基于Kullback-Leiber距離的遷移仿射聚類算法

畢安琪 王士同

畢安琪, 王士同. 基于Kullback-Leiber距離的遷移仿射聚類算法[J]. 電子與信息學(xué)報(bào), 2016, 38(8): 2076-2084. doi: 10.11999/JEIT151132
引用本文: 畢安琪, 王士同. 基于Kullback-Leiber距離的遷移仿射聚類算法[J]. 電子與信息學(xué)報(bào), 2016, 38(8): 2076-2084. doi: 10.11999/JEIT151132
BI Anqi, WANG Shitong. Transfer Affinity Propagation Clustering Algorithm Based on Kullback-Leiber Distance[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2076-2084. doi: 10.11999/JEIT151132
Citation: BI Anqi, WANG Shitong. Transfer Affinity Propagation Clustering Algorithm Based on Kullback-Leiber Distance[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2076-2084. doi: 10.11999/JEIT151132

基于Kullback-Leiber距離的遷移仿射聚類算法

doi: 10.11999/JEIT151132
基金項(xiàng)目: 

國家自然科學(xué)基金(61170122, 61272210),江蘇省 2014 年度普通高校研究生科研創(chuàng)新計(jì)劃項(xiàng)目(KYLX_1124),山東省高等學(xué)校科技計(jì)劃項(xiàng)目(J14LN05)

Transfer Affinity Propagation Clustering Algorithm Based on Kullback-Leiber Distance

Funds: 

The National Natural Science Foundation of China (61170122, 71272210), Jiangsu Graduate Student Innovation Projects (KYLX_1124), The Science and Technology Program Shandong Provinceial Higher Education (J14LN05)

  • 摘要: 針對遷移聚類問題,該文提出一種新的基于Kullback-Leiber距離的遷移仿射聚類算法(TAP_KL)。該算法從概率角度重新解釋AP算法的目標(biāo)函數(shù),并借助于信息論中最常見的一種距離度量,即Kullback-Leiber距離,測量源域與目標(biāo)域代表點(diǎn)的相似性。另外,通過詳細(xì)分析TAP_KL算法與AP算法的目標(biāo)函數(shù),得出一個(gè)重要結(jié)論,即可以將源域與目標(biāo)域的相似性嵌入到目標(biāo)域數(shù)據(jù)集相似性矩陣的計(jì)算中,從而直接利用AP算法的優(yōu)化算法優(yōu)化TAP_KL算法的目標(biāo)函數(shù),解決基于代表點(diǎn)的遷移聚類問題。最后,通過基于4個(gè)數(shù)據(jù)集的仿真實(shí)驗(yàn),進(jìn)一步驗(yàn)證了TAP_KL算法在解決遷移聚類問題時(shí)的有效性。
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出版歷程
  • 收稿日期:  2015-10-10
  • 修回日期:  2016-04-17
  • 刊出日期:  2016-08-19

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