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 article discussed two data mining algorithms: the classification tree and clustering.
本文讨论了两种数据挖掘算法：分类树和群集。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
数据挖掘通常涉及到一些标准的任务，包括聚集、分类、回归分析和关联性规则学习。
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。
The new data has no classification (in this case, no checks on heart disease have been made) and the scoring process assigns a prediction to each new record according to the mining model.
新的数据没有分类别（这里是指还没有做过心脏病检查），评价过程根据挖掘模型将一个预测赋给每个新的记录。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
目的：探讨带先验知识的支持向量机（P-SVM）数据挖掘算法在中医证候信息自动分类中的应用。
Decision tree algorithms are applied to the data mining of the mammography classification, proposes a medical images classifier based on decision tree algorithm, the experiment results are given.
利用决策树算法对乳腺癌图像数据进行分类，实现了一个基于决策树算法的医学图像分类器，获得了分类的实验结果。
A new sampling method is proposed, which USES the latest technologies of database. It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
Classification is an important problem in data mining.
分类是数据挖掘领域中的一个重要研究课题。
Classification is one of the most basic tasks during the biological statistics and data mining.
在生物统计以及数据挖掘中，分类预测是最基本的任务之一。
Classification is one of important methods used in data mining.
分类是数据挖掘中的一种非常重要的方法。
Link based classification is an important research direction in link mining.
基于链接分类是链接挖掘的一个重要方向。
Each mode has its own emphasis, among them, there are some already studied modes have much more research outcome, such as some methods in association rule mining, classification and forecast mode.
各种模式各有侧重，其中有一些已经研究得较为成熟，研究成果也较多，如挖掘关联规则、预测方法和分类模式中的一些其他方法。
Data classification is one of important contents from Data mining.
数据分类是数据挖掘中一个重要的内容。
The paper mainly discusses the present application situation and classification of filling mining method at home and abroad and the development prospects of this technology.
本篇文章主要介绍了充填采矿法在海内外的应用现状及分类，并展望了这项技术的未来发展前景。
Several major kinds of data mining methods, including characterization, classification, association rule, clustering, outlier detection, pattern matching, data visualization, and so on.
常用的数据挖掘方法包括描述、分类、关联规则、聚类、孤立点检测、模式匹配、数据可视化等。
Those are tightly associated with classification algorithm on the view of data mining.
从数据挖掘的观点来看，它们都与分类算法密切相关。
This paper presents a classification method for data mining based on BP neural network, and puts forward improvement ideas.
本文介绍一种基于BP神经网络的数据挖掘的分类方法，并提出了改进思想。
There are some various algorithms in data mining, and decision tree classification algorithm is the most popular one.
在数据挖掘中存在多种算法，决策树分类算法是应用比较多的一种。
Experiment shows that the classification rule mining method using hybrid genetic algorithms can find a set of the succinct, accurate and comprehensible classification rules.
实验表明，基于混合遗传算法的分类规则挖掘方法能够从数据集中发现一个简洁、准确、易理解的规则集。
The paper proposed an algorithm based on ant colony algorithm for mining classification rule from the Student Scores Management Database.
本文采用一种基于蚁群算法的分类规则挖掘算法，其特征实质上是一种序列覆盖算法。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
This paper studies data mining classification calculation of SLIQ.
本文研究基于SLIQ的数据挖掘分类算法。
It is widely used for sieving and classification in the industry of mining, building materials, traffic, energy, and chemical industry.
它广泛用于筛选和分类，在行业中的采矿业，建材，交通，能源，化工等行业。
In the second and third chapters it introduces data mining and related problems, including the process, method, classification and application of data mining.
在第二章我介绍了数据挖掘及其相关问题，包括数据挖掘的过程、方法、分类和应用等。
Then the method of synchronous amalgamating is chosen to implement the mining of classification rules from multiple data sources.
最后，选择规则的同步融合策略实现多数据源中的分类规则挖掘。
This article mainly refers to the basic concept, classification and process of web data mining, as well as its application in e-commerce.
主要介绍网络数据挖掘的基本概念、分类、挖掘的过程及其在电子商务中的应用。
This paper comprehensively introduces the concept, classification, task, methods and pricipal applications of data mining.
本文综合介绍了数据挖掘的概念、分类、任务和方法，并展示了其丰富的应用领域。
Classification is an important task in data mining field, how to discover the intelligible and interesting classification rules is one of the main problems facing data mining.
分类是数据挖掘的一项重要任务，如何发现可理解的、令人感兴趣的分类规则是数据挖掘面临的一个主要问题。
Classification is an important task in data mining field, how to discover the intelligible and interesting classification rules is one of the main problems facing data mining.
分类是数据挖掘的一项重要任务，如何发现可理解的、令人感兴趣的分类规则是数据挖掘面临的一个主要问题。
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