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

页码：127 / 131

页数：5

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