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(chēng)概念提升）是一種廣泛使用的知識(shí)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(kāi)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(guò)概念提升及刪除無(wú)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。