基于形式Context的格聚类与特征逼近判别

LATTICE-CLUSTER MODEL AND CHAR-ACTERISTIC APPROXIMATING MODEL BASE ON CONTEXT

本文建立一个基于 Guo- Qiang Zhang[2 ]理论的格聚类模型与特征逼近判别模型 .如果一个统计背景 ET被解释为一个 Context CET=(Po,| =Pa) ,那么基于形式 Context的格聚类模型完全是 [FCA]的外延和内涵统一的具体表达 ,而特征逼近判别模型则是从语义谓词逻辑出发的判别方法 ,用有限特征逼近解决了无限属性的实际应用困难 .

This paper constructs the lattice cluster model and characteristic approximating mode from Guo Qiang Zhang[2]. When a statistical economic case ET is translated into a Context C ET =(P o,|=, P a), the lattice cluster model expresses that the intent of concept is consistent with the extent of concept. The characteristic approximating model is scientific statistical discriminance which reflects rules of predicate logic.