Classification trees are often used in pattern recognition to speed up the classification.
模式识别中分类树方法可用于提高模式分类的速度。
This brings up another one of the important concepts of classification trees: the notion of pruning.
这还引出了分类树的另一个重要概念：修剪。
Future articles will touch upon other methods of mining data, including clustering, Nearest Neighbor, and classification trees.
本系列后续的文章将会涉及挖掘数据的其他方法，包括群集、最近的邻居以及分类树。
Objective:To introduce the basic principle of tree-structured methods, and then use classification trees to analyze a real example in medical research.
目的：介绍树结构法的基本原理与方法，并用分类树法对医学研究中的实例进行分析。
Classification (also known as classification trees or decision trees) is a data mining algorithm that creates a step-by-step guide for how to determine the output of a new data instance.
分类(也即分类树或决策树)是一种数据挖掘算法，为如何确定一个新的数据实例的输出创建逐步指导。
This model can be used for any unknown data instance, and you are able to predict whether this unknown data instance will learn classification trees by asking them only two simple questions.
这个模型可用于任何未知的数据实例，来预测这个未知数据实例是否通过只询问两个简单问题就能理解分类树。
Users snap photos of local birds, plants, trees, and other species, and can either identify the organism or leave the classification up to the crowd.
用户可以拍下当地鸟类、植物、树木和其他生物的照片，然后对该生物进行鉴别，或者把鉴定工作留给其他人完成。
Discusses the classification and regression trees method, introduces its application in developing universities 'science research decision support system.
讨论了分类回归树方法，并介绍了它在开发高校科研决策支持系统中的应用。
Generally, the learned model can represent by classification rules, decision trees, or mathematical formulae.
通常，模型可以用分类规则、判定树或数学公式表示。
Based on thought of multiple classifiers combination method, this paper proposes a combination classification method of multiple decision trees based on PSO Algorithm.
针对数据挖掘中的分类问题，依据组合分类方法的思想，提出一种基于遗传算法的多重决策树组合分类方法。
Decision trees and their ensembles are popular methods for the machine learning tasks of classification and regression.
决策树和决策树的组合，是解决分类问题和回归问题比较流行的一类算法。
This paper describes a method which has been used for stand population selection and classification based on the plus trees selection principle of a single tree.
本文将林木树种单株选优原则和方法运用到林木群体选择和划分上。
Real biological data experiments have shown that this classification method outperformed than single neural networks, 1-nearest-neighbor classifiers and decision trees.
实际的生物学数据实验表明该方法性能优于单个神经网络，最近邻法和决策树。
Real biological data experiments have shown that this classification method outperformed than single neural networks, 1-nearest-neighbor classifiers and decision trees.
实际的生物学数据实验表明该方法性能优于单个神经网络，最近邻法和决策树。
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