Acquiring hyperspectral remotely sensed image classification rules using inductive learning

摘要

In this paper, an 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.