( 4 ) choose the attribute in which the number of the equivalence is largest as the main attribute ( 4 )计算每个属性的等价类数目，选择等价类数目最多的属性作为主属性。
For the aggregate function median , the concept of a pseudo class is introduced to further reduce the size of the quotient cube 当从quotient数据立方体中删除元组的时候，有些等价类需要进行合并。
The theory of linear series of the piecewise algebraic curve is a kind generalization of that of linear series of the algebraic curve ( [ 71 ] ) 分片代数曲线的完全列是由所有属于同一等价类的有效正常循环以及所有与它特等价的有效奇异循环构成。
The approach to classification based on the equivalence classes of the main attribute is as follows : ( 1 ) discretize the continuous training data 以某属性的等价类(相近类)组成的子集作为svm的训练集预分类的方法如下。 ( 1 )将连续性训练数据离散化。
For example , a reasonably trained , reasonably motivated programmer can do a perfectly fine job finding boundary conditions and checking whether each known equivalence class is handled 例如，一个接受过一定培训、有一定积极性的程序员可以很好地找到边界条件，并且检查每一个等价类是否都处理了。
Then we have searched out all of the unequal complementary sequence pairs with length up to 20 . we have got some suppositions from the searching results , though the correctness of it is waiting for prove 并由此设计了最佳二元互补序列偶的快速搜索算法，搜索出长20以内的所有最佳二元互补序列偶的等价类。
The invariant ( v ( a ) , [ 1a ] ) that we used for unital case is the semigroup of murry - von neumann equivalence classes of projections in matrices over c * - algebras together with the class of the unit 我们用来分类的不变量( v ( a ) ， [ 1 _ a ] ) (有单位元的情况)是a的矩阵代数中所有投影的murry - vonneumann等价类所成的半群及单位元所在的等价类。
The batch algorithm in this paper reduces the redundant computation in each node for generating its children by the presented definition of expansion - equivalence class , thereby improves the algorithm ? efficiency 而本文中批生成算法通过提出的扩展等价类这一概念来有效地减少了在每个节点处计算其子节点的冗余计算量，从而达到提高算法效率的目的。
Concept lattice and rough set have many common characteristics in data analysis . and some characters of rough set such as equivalent class , upper and under approximate all can be represented by concept lattice 在概念格与粗糙集的关系方面，由于概念格与粗糙集在数据分析方面有相似之处，并且粗糙集的一些概念包括等价类，上、下近似等都可以通过概念格来表示。
Classification model is based on typical rough set theory and entropy theory , select the attribute according to entropy theory , determine the equivalence classes according to indiscernible relation , then extract the classification rules 分类模型是以经典的粗糙集合理论和信息熵理论为基础，依据信息熵理论对属性进行筛选，依据不可区分关系确定等价类，从而提取决策规则。
