Acquiring hyperspectral remotely sensed images classification rules using inductive learning

被引：1
|
作者：
Sun, LX [1 ]
Zhang, YM [1 ]
机构：
[1] Harbin Engn Inst, Dept Surveying Engn, Harbin 150008, Peoples R China
来源：
HYPERSPECTRAL REMOTE SENSING AND APPLICATIONS | 1998年 / 3502卷
关键词：
remote sensing; classification; extension matrix; rough set; discretization;
D O I：
10.1117/12.317795
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
In this paper, a extension matrix based rule inductive learning algorithms have been presented. Exception the introduction of this rule inductive learning algorithm, we proposed a novel algorithm for discreting continuous valued attributes which is essential preprocessing step for applying symbol rule inductive algorithms to remotely sensed data analysis. Some initial results are finally given which can demonstrate the advantages of rule-based classification.
引用
收藏
页码：164 / 168
页数：5
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