Clustering-and-selection model for classifier combination

被引：0
|
作者：
Kuncheva, LI [1 ]
机构：
[1] Univ Wales, Sch Informat, Bangor LL57 1UT, Gwynedd, Wales
来源：
KES'2000: FOURTH INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ENGINEERING SYSTEMS & ALLIED TECHNOLOGIES, VOLS 1 AND 2, PROCEEDINGS | 2000年
关键词：
multiple classifier systems; classifier combination; classifier selection; clustering and selection;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We devise a simple clustering-and-selection algorithm based on a probabilistic interpretation of classifier selection. First, the data set is clustered into K clusters and then the most successful classifier for a given cluster is nominated to label the inputs in the Voronoi cell of the cluster centroid. The proposed method is compared experimentally with minimum, maximum, product and average. Given are also the results from the Naive Bayes method, Behavior-Knowledge Space (BKS) method, the best individual and the oracle.
引用
收藏
页码：185 / 188
页数：4
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