本文讨论了两种数据挖掘算法：分类树和群集。
This article discussed two data mining algorithms: the classification tree and clustering.
聚类算法是数据挖掘算法中的重要解决方法。
Clustering algorithm is an important one in data mining methods.
OLAM挖掘机制的核心是高效的数据挖掘算法。
多关系数据挖掘算法的搜索空间变得更大、更复杂。
The search space of Multi-relational data mining algorithm becomes larger and more complex.
并具体分析比较了多种的典型聚类和决策树数据挖掘算法。
Some classical clustering algorithms and decision trees algorithms are analyzed and compared.
传统的数据挖掘算法是在数据库的一张单一的表中查找模式。
Typical data mining approaches look for patterns in a single relation of a database.
实验结果显示了基于群体智能的离群数据挖掘算法的有效性。
Results show that the validity of outlier mining algorithm based on swarm intelligence.
本文重点对空间数据挖掘算法及其与GIS的集成进行了研究。
This paper places great emphasis on the study of the spatial data mining methods and their integration with GIS.
然后，总结了流数据挖掘算法的特点，并给出了算法中常用的技术。
Then the characters of stream data mining algorithms are summarized and several techniques that are used in these algorithms are introduced.
根据课题背景，给出一个针对时序数据的离群数据挖掘算法的改进算法。
Based on the project background, an improved outlier data mining algorithm for time series data is given out.
在研究多段支持度数据挖掘算法的基础上提出并行挖掘相联规则的算法。
A parallel algorithm for discovering association rules is presented, after an algorithm based on calculating multi-segment support has been studied.
设计了基于加权快速聚类的异常数据挖掘算法，以便能快速发现异常数据。
This article promoted outlier data mining algorithms based on weighted fast clustering to inspect and deal with outlier data effectively.
InfoSpherewarehouse几乎包含目前所有数据挖掘算法的极为高效的实现。
InfoSphere Warehouse contains highly efficient implementations of almost all current data mining algorithms.
本文把模糊集理论和传统的关联挖掘结合在一起，提出了一种模糊关联数据挖掘算法。
In this paper, we connected fuzzy set theory with association mining, and proposed a fuzzy association data mining arithmetic.
其次介绍了数据挖掘的相关问题以及主流的数据挖掘算法，并分析了各类算法的优缺点。
Secondly discusses data mining related knowledge as well as the mainstream algorithms, and analyzes each kind of algorithms good and bad points.
介绍了人工智能领域最新的基于结构风险最小化原理的数据挖掘算法——支持向量机算法。
Based on the structural risk minimization principle, the latest data mining method, support vector machine (SVM) algorithm, in artificial intelligence field was introduced in this paper.
同时，由于糖尿病数据的连续性，选用了决策树方法中的c4.5算法作为数据挖掘算法。
Also, for the continuity in Diabetes Mellitus data, choosing the C4.5 algorithm in Decision Tree method to be the data mining algorithm.
传统数据挖掘算法是面向关系数据库和数据仓库的，不能直接用于XML文档的数据挖掘。
Traditional data mining algorithm is oriented relational database and data warehouse, and can not be directly used for data mining in XML documents.
与传统的数据挖掘算法相比，多关系数据挖掘特有的复杂性对算法的性能提出了更高的要求。
Compared to the traditional data mining algorithms, the complexity of specific performance of the algorithm in the multi-relational data mining put forward higher requirements.
介绍了数据挖掘技术的背景、概念、流程、数据挖掘算法，并阐述了数据挖掘技术的应用现状。
This paper introduces the background, concept and process of data mining technology and data mining algorithms, and elaborates the application actuality of data mining technology.
属性约简是数据挖掘预处理中非常重要的一步，它通过减少信息的维数提高数据挖掘算法的效率。
Attribute reduction is one of important step in preprocessing of data mining, it improves the efficiency of the data mining algorithm by reducing the dimensions of the information.
提出了关键技术，包括：挖掘主题的定义方法、海量训练样本的在线生成和高性能数据挖掘算法。
The key technologies is proposed, including methods of definition of mining topics, online acquirement of extra large amount of training samples, and algorithms of data mining with high performance.
结合某汽车制造企业ERP系统的具体情况，编制程序实现了上述数据挖掘算法与ERP系统的整合。
Then considering the concrete case of a manufacture enterprise, these algorithms of data mining are integrated with erp system by computer programming.
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。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
提出了一种基于动态规划和动态时间弯折函数的数据挖掘算法，并应用该算法对股市进行技术分析。
A new data-mining algorithm based on dynamic programming and dynamic time warping function was proposed and applied in technical analysis of stock market.
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。
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.
只要遵循该平台的数据模型接口和挖掘模型接口，新的数据挖掘算法可以很容易地集成到该平台中去。
New data mining algorithms can easily be integrated into this platform if they comply with the data model interface and mining model interface of this platform.
论文把分布式数据挖掘算法运用于入侵检测系统，研究了基于分布式关联规则算法的分布式模式提取。
This paper applies distributed data mining algorithm to IDS, takes some research on distributed pattern extraction which is based on distributed association rules algorithm.
论文把分布式数据挖掘算法运用于入侵检测系统，研究了基于分布式关联规则算法的分布式模式提取。
This paper applies distributed data mining algorithm to IDS, takes some research on distributed pattern extraction which is based on distributed association rules algorithm.
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