decision tables
英 [dɪˈsɪʒn ˈteɪblz]
美 [dɪˈsɪʒn ˈteɪblz]
决策表
双语例句
- 1 Decision tables offer a simple, visual aid, and they can be applied in knowledge-based systems to perform verification processes efficiently.
1决策表提供了一个简单的，可视化的帮助，它可以在知识库系统中被使用，来高效的执行验证过程。 - This category includes if-then statements and decision tables.
这个类别包括if-then语句和决策表。 - It is easy to consider new combinations of input data and to extend the test suite coverage, adding new conditions in the decision tables.
这样可以轻松的合并输入的数据和扩大测试套件的范围，并在决策表中添加新条件。 - The most common artifacts provided by almost every industry-leading BRM tool are rule and rule-set templates, decision tables, and decision trees.
几乎所有业界领先的BRM工具都提供的最常用构件是规则和规则集模板、决策表和决策树。 - When the decision table becomes too complex, a hierarchy of new decision tables can be constructed.
当决策表变得复杂时，一个新的决策表层级就会被创建。 - Most rule management environments have useful capabilities to manage compound rules, decision tables, and interdependent rule elements.
许多规则管理环境能够管理复合规则、决策表和相互依赖的规则元素。 - Deterministic decisions where rules can be described in "if then" constructs, decision tables or decision trees.
规则可以在“ifthen”结构、决策表或决策树中描述决定性的决策。 - Services to explore the decision tables and to compare alternatives with verifications performed on the AUT
浏览决策表并比较AUT中执行的验证选择 - In decision tables, rows and columns represent different conditions and the resulting action is defined by their intersections.
在决策表中，行和列表示不同的条件，而结果操作由它们的交点来定义。 - A testing logic easy to keep track of and to change with the decision tables that can be read and filled out by non-programmers
测试逻辑可以很容易地使用决策表进行追踪与变更，这样可以被非程序员阅读和填写 - Examples of artifacts from BRM tools include rule sets, decision tables, decision trees, and score cards.
BRM工具中的构件示例包括规则集、决策表、决策树和记分卡。 - Create the decision scripts with a code template and fill the decision tables
使用一个代码模版建立决策脚本，并填写决策表 - Decision tables provide compact visualizations of orthogonal conditions.
决策表可提供正交条件的精简可视化表示。 - Similar content as Decision Tables, but represented as a tree with branching logic.
这种形式与决策表相似，但是表示为树型，可以包含分支逻辑。 - Knowledge Acquisition from Decision Tables Containing Continuous-Valued Attributes
连续值属性决策表中的知识获取方法 - Attribute Reduction Algorithm Based on Relative Granularity in Decision Tables
一种基于相对粒度的决策表约简算法 - The scope of possibility ranges from a textual description ( using a rule specific language or plain English) to the use of decision tables or decision trees.
从文本描述（使用一种特定于规则的语言或者简单英语），到决策表或者决策树的使用，都有可能。 - An Improved Algorithm of Attribute Reduction Aimed at Incompatible Decision Tables
一种针对不相容决策表的属性约简改进算法 - Much valuable but hidden information can be discovered from decision tables associated with compatible reduction and lower approximation reduction based on dominance relation.
定义了决策表在优势关系下的相容约简和下近似约简，优势关系下的相容约简是优势关系下一致决策表约简的推广。 - Ordered assignment reduction is defined in inconstant decision tables.
在不一致决策表中定义了分配序约简，给出分配序一致集的判定定理。 - As a method for dealing with indefinite information, previous rough set only concerns with complete decision tables.
粗集是处理不确定信息的有效方法，但它通常适用于完全决策表。 - The main content of the paper is as follows: Firstly, this paper introduces the knowledge representation system and decision tables and the concept of decision table reduction, then puts forward the algorithm for each phase of the reduction.
本文主要内容如下：首先引入了知识表达系统和决策表，介绍了决策表简化的概念并提出了其简化各阶段相应的算法。 - This method can easily build fuzzy decision tables and reduce decision tables based on fuzzy set theory and rough set theory.
该方法结合模糊集和粗糙集理论，由模糊聚类得出模糊决策表，并可以方便地构造决策表和对决策规则表进行简化。 - In this paper, by using connection degree of set pairs upper approximation and lower approximation are defined in the system, then decision tables are analyzed in this case, and distribution reduction, assignment reduction are presented.
利用集对联系度定义了多值信息系统的上、下近似运算，并对这种情况下的决策表进行分析，根据该模型的特点提出了α分布约简和α分配约简。 - The thesis proposes a rough set approach to mining minimal rules in inconsistent decision tables MIE-RS.
作者提出了从不一致决策表中挖掘最简规则的粗糙集方法MIE-RS。 - This algorithm not only can be applied in consistent decision tables, but also inconsistent decision tables.
该算法不仅可以处理一致决策表还可以处理不一致决策表。