提出了一种基于熵理论的BP神经网络结构设计修剪算法。
A pruning algorithm based on entropy theory for designing BP neural network structure is proposed.
在树的修剪阶段，采用了一种基于最小描述长度原理的修剪算法。
A pruning algorithm based on the principle of Minimum Description Length is applied in the tree-pruning phase.
针对一类常见而简单的规则中有项或缺项的约束，提出了一种基于事务数据修剪的约束关联规则的快速挖掘算法。
Aiming at a familiar and simple constraint that some items must or must not present in rules, a fast clipped-transaction-based constraint association-rule mining algorithm was put forward.
现有的传统关联规则挖掘算法构建频繁候选项的方式和修剪技术是其应用于空间数据挖掘的技术难题。
The way of generating frequent candidate a nd pruning technology are difficult technical problem when prenest traditional association rules mining algorithm is used to spatial data mining.
为了构建聚类代表，算法通过构造最佳匹配树，合并树，修剪树三步来实现。
The cluster representative was constructed by three successive steps named Tree matching, Tree merging and Tree pruning.
为了构建聚类代表，算法通过构造最佳匹配树，合并树，修剪树三步来实现。
The cluster representative was constructed by three successive steps named Tree matching, Tree merging and Tree pruning.
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