强度的几种度量由关联的挖掘算法进行计算。
Several measures of the strength are calculated by the association's mining algorithm.
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.
文章还给出相应的挖掘算法。
提出了事务间量化关联规则的挖掘算法。
The algorithm of mining inter-transactional quantitative association rules is propose.
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.
提出了一种基于关联矩阵的频繁子图挖掘算法。
An algorithm for mining frequent subgraphs based on associated matrix was proposed.
目的提出基于关系代数理论的关联规则挖掘算法。
Aim To put forward association rule mining algorithm based on relation algebra theory.
OLAM挖掘机制的核心是高效的数据挖掘算法。
查询主题使用存储过程访问由挖掘算法创建的集群模型的集群信息。
A query subject that USES a stored procedure to access the cluster information of the clustering model created by the mining algorithm.
关联规则挖掘算法是通信网告警相关性分析中的重要方法。
Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis.
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.
本文提出了一个基于反向矩阵的最大频集的交互式挖掘算法。
In this paper, an algorithm based on inverted matrix for interactive mining is proposed.
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.
本文在支持度和置信度的框架内开展了对频集挖掘算法的研究。
Studies in this paper are made within the framework of support and confidence.
随着数据量的增加，挖掘算法处理海量数据的能力问题日益突出。
The ability of data mining algorithms to deal with mass-data becomes more important with the increase in data.
提高序列模式挖掘算法效率的关键在于减少发现频繁序列的时间。
To speed up mining sequential patterns, reducing the time cost is very important during discovering sequential frequent sequence.
提出一种新的基于符号化表示的时间序列频繁子序列的挖掘算法。
This paper proposes a new algorithm for mining frequent subsequence in time series based on symbolic representation.
在序列模式的增量式挖掘算法中，IUS算法是目前最为先进的算法。
Of all the incremental mining algorithms, the IUS is the most advanced at present.
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.
通过采用二进制串表示所定义的信息粒，提出了基于粒计算的关联规则挖掘算法。
Through defining information granule with binary string, we introduce an algorithm of mining association rules based on granular computing.
提出了基于云的网络安全态势预测思想和基于云的网络安全态势预测规则挖掘算法。
The thought of network security situation prediction based on cloud and an algorithm of network security situation prediction based on cloud were proposed.
首次提出了利用幂集作为挖掘关联规则的工具，给出了基于幂集的关联规则挖掘算法。
This paper firstly presents a power set-based association rules mining algorithm which USES pow er set as an association rules mining tool.
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.
本文的内容包括两个方面：关联规则挖掘算法研究和数据挖掘应用系统体系结构的研究。
The content of this paper includes two respects: research of data mining algorithms and the system structure of the application platform of data mining.
结合笔者研究工作，主要介绍了文本挖掘的研究内容，挖掘过程，挖掘算法及应用前景。
This paper mainly introduces the research contents on text mining, mining process, mining algorithm and application foreground combined with our research work.
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.
挖掘序列模式是数据挖掘的主要内容之一，目前已有许多序列模式模型和相应的挖掘算法。
Mining sequential patterns is one of the central content in data mining. There have been many models of sequential patterns and algorithms for mining sequential patterns.
这也是我想审慎地告诉大家的一点：有时候，将数据挖掘算法应用到数据集有可能会生成一个糟糕的模型。
That takes us to an important point that I wanted to secretly and slyly get across to everyone: Sometimes applying a data mining algorithm to your data will produce a bad model.
这也是我想审慎地告诉大家的一点：有时候，将数据挖掘算法应用到数据集有可能会生成一个糟糕的模型。
That takes us to an important point that I wanted to secretly and slyly get across to everyone: Sometimes applying a data mining algorithm to your data will produce a bad model.
应用推荐