在数据挖掘中，决策树方法是一个重点研究方向。
In data mining, decision tree algorithm is a key research direction.
决策树方法是数据挖掘的一种方便而实用的方法。
Decision tree is a convenient and practical method for data mining.
本文首先详细介绍了数据挖掘技术及其中的决策树方法。
This paper firstly introduces the principle of Data Mining technology and the decision tree method.
决策树解决方法的复杂度是多少？
决策树是机器学习和数据挖掘领域中一种基本的学习方法。
Decision tree is a basic learning method in machine learning and data mining.
决策树是数据挖掘中的常用方法。
介绍了决策树量化的方法，给出了量化的公式和实例。
Decision tree quantification method is introduced and quantification formula and examples are also given.
因此，决策树是一种简便可行的计算机辅助诊断方法。
Therefore, the decision tree method is a simple and useful tool for computer-aided diagnosis.
决策树是分类数据挖掘的重要方法。
Decision tree is one of the important Categorising Data Mining methods.
对决策树剪枝方法进行研究。
决策树分析法是决策的有效方法之一。
Decision, tree is one of the efficient methods of decision making.
提出一种并行的决策树学习方法。
A new parallel learning method of the decision tree is proposed in this paper.
而且这种方法得到了一个基于情感选择的二叉决策树。
This method has been an emotional choice based on the binary decision tree.
摘要：决策树是数据挖掘任务中分类的常用方法。
Absrtact: The decision tree is a usual method of classification in data mining.
决策树是数据挖掘和归纳学习的重要方法。
Decision tree is an important method for data mining as well as induction learning.
决策树是一种采用分治策略的聚类分析方法，构建决策树的关键是选择合适的属性。
One of the best ways to analyze a decision is to use so-called decision trees.
实验结果表明，这种方法构造的SVM决策树分类器分类性能较好。
The results of experiment demonstrate that the SVM decision tree built up by...
实验结果表明，这种方法构造的SVM决策树分类器分类性能较好。
The results of experiment demonstrate that the SVM decision tree built up by...
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