classification decision tree 分类决策树
classification decision making 分类决策
multi-classification decision tree 多分类决策树
multi classification decision tree 多分类决策树
multi-criteria classification decision-making 多准则分类决策
Decision tree classification 决策树分类法 ; 决策树分类挖掘
Firstly,generates fuzzy rules base using fuzzy clustering from numerical sample dates,and then simplifies the sample attributions using rough set theory,deletes the redundant rules,and gets the simplified fuzzy rules base,in order to make classification decision conveniently.
对于数值型样本数据,首先采用模糊聚类生成模糊规则库,然后运用粗糙集理论对样本属性进行约简,删除冗余规则,即可得到精简的模糊规则库,以方便进行分类决策。
参考来源 - 一种基于精简的模糊规则库的分类算法·2,447,543篇论文数据，部分数据来源于NoteExpress
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification decision tree.
提出了一种融合无监督和监督两种学习策略生成多分类决策树的方法。
This paper introduces two construction algorithms of Classification decision tree based on parallel algorithm, and analyzes applicability.
本文重点介绍了两种基于并行算法的分类决策树的构造算法，并对它们的适用性及特点作了分析。
As for the problem above, the paper in-depth researches one of the core algorithms which are applied to classification-decision tree algorithm.
本文从这一实际问题出发，对数据挖掘中用于分类的核心算法之一——决策树方法进行了深入地研究。
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