On-line feature and classifier selection for agricultural produce

被引：0
|
作者：
Laykin, S [1 ]
Edan, Y [1 ]
Alchanatis, V [1 ]
机构：
[1] Ben Gurion Univ Negev, Dept Ind Engn & Management, IL-84105 Beer Sheva, Israel
来源：
Proceedings of the Eighth IASTED International Conference on Artificial Intelligence and Soft Computing | 2004年
关键词：
unsupervised classification; classifier selection; fuzzy rule-based system and feature 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：
This paper presents an on-line hierarchical classifier for agricultural products. The classifier consists of two levels. The first level detects new populations using an on-line clustering algorithm. The second level selects the best-fit classifier using a fuzzy system. This paper presents the combination of the two levels into a complete system. Feature selection is conducted on-line according to the classified population. A synthetic dataset is used to estimate the classifier capabilities and compare it to previous results. Results indicated that the combined online system results in improved classification accuracy.
引用
收藏
页码：127 / 131
页数：5
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