控制与决策
控製與決策
공제여결책
CONTROL AND DECISION
2013年
6期
904-908
,共5页
半监督聚类%主动式学习%成对约束%谱聚类
半鑑督聚類%主動式學習%成對約束%譜聚類
반감독취류%주동식학습%성대약속%보취류
semi-supervised clustering%active learning%pairwise constraint%spectral clustering
针对半监督聚类学习算法中缺乏主动学习的缺陷,提出一种纠错式主动学习成对约束方法.算法通过寻找一般聚类算法自身难以发现的成对约束信息,同时避免这部分约束信息之间本身的关系,将其引入谱聚类算法,利用该监督信息调整谱聚类中点与点之间的距离矩阵对两点间距离进行排序,采用双向寻找的方法,使得学习器即使接收到没有标记的数据也能进行主动学习.实验分析表明,所提出算法能够获得较为满意的聚类效果.
針對半鑑督聚類學習算法中缺乏主動學習的缺陷,提齣一種糾錯式主動學習成對約束方法.算法通過尋找一般聚類算法自身難以髮現的成對約束信息,同時避免這部分約束信息之間本身的關繫,將其引入譜聚類算法,利用該鑑督信息調整譜聚類中點與點之間的距離矩陣對兩點間距離進行排序,採用雙嚮尋找的方法,使得學習器即使接收到沒有標記的數據也能進行主動學習.實驗分析錶明,所提齣算法能夠穫得較為滿意的聚類效果.
침대반감독취류학습산법중결핍주동학습적결함,제출일충규착식주동학습성대약속방법.산법통과심조일반취류산법자신난이발현적성대약속신식,동시피면저부분약속신식지간본신적관계,장기인입보취류산법,이용해감독신식조정보취류중점여점지간적거리구진대량점간거리진행배서,채용쌍향심조적방법,사득학습기즉사접수도몰유표기적수거야능진행주동학습.실험분석표명,소제출산법능구획득교위만의적취류효과.
@@@@An active learning algorithm based on pair-wise constraints with error correction is proposed in this paper. The algorithm searches the pair-wise constraints information that the clustering algorithm cann’t find, and tries its best to reduce the connections between these constraint informations, which is used in the spectral clustering. The suppervised information is used to adjust the distance matrix in the spectral clustering, and the distances are sorted. The learninger can study actively when the learinger receives the data without flags by using the two-way search method. Experiment analysis shows that better clustering result can be obtained by using the proposed method.
