concept generalization

基本解釋

Attribute-oriented induction (concept generalization) is a kind of KDD method widely used.
面向?qū)傩缘臍w納學(xué)習(xí)（亦稱概念提升）是一種廣泛使用的知識發(fā)現(xiàn)方法。
In data mining with Attribute-Oriented Generalization(AOG), attribute reduction and concept generalization can not part from concept hierarchy.
在面向?qū)傩詺w納（AOG）的數(shù)據(jù)挖掘中，屬性歸約及概念歸納都離不開概念層次。
Through concept generalization and deleting irrelevant dimension, various association rules less than 7D can be evolved from the 7D image association rules model 7D_AR.
通過概念提升及刪除無關(guān)維，由七維圖像關(guān)聯(lián)規(guī)則模型7D_AR可以演化出維數(shù)小于七維的各種關(guān)聯(lián)則。