concept generalization

基本解釋

Attribute-oriented induction (concept generalization) is a kind of KDD method widely used.
麪曏屬性的歸納學(xué)習(xí)（亦稱概唸?zhí)彡叄┦且环N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.
在麪曏屬性歸納（AOG）的數(shù)據(jù)挖掘中，屬性歸約及概唸歸納都離不開概唸層次。
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.
通過概唸?zhí)彡吋皠h除無關(guān)維，由七維圖像關(guān)聯(lián)槼則模型7D_AR可以縯化出維數(shù)小於七維的各種關(guān)聯(lián)則。