研究如何利用分类挖掘来进行网关转发性能的判定。
This paper studies on using Class Mining for decision-making of gateway transmitting performance.
针对丙酮精制过程的特点，提出一种基于神经网络的丙酮产品质量分类挖掘方法。
Considering the features of acetone refining process, a strategy of neural network based data mining for product quality classification is proposed.
概念漂移是数据流分类挖掘中的一个难点，它是伴随着数据流的时变性而产生的。
Concept drift, as a difficult point in the field of data stream mining, is generated with the accompany of time-varying data streams.
在分类挖掘的预处理过程中，重要的是如何选择最有效的特征子集，以便于分类学习与预测。
During the preprocessing of classification, it is important to select feature subset effectively, in order to classification learning and predicting.
在系统上对各类远程教育站点上收集的文本资料信息自动进行分类挖掘，取得了较好的实验效果。
The system classifies the text resource information collected from all kinds of remote education websites, and good experiment results have been got.
围绕着分类挖掘中的隐私保护问题展开研究，给出了一种基于数据处理和特征重构的朴素贝叶斯分类中的隐私保护方法。
This paper focuses on privacy preserving classification, and presents a privacy preserving Naive Bayes classification approach based on data randomization and feature reconstruction.
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.
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。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
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。
Future articles will touch upon other methods of mining data, including clustering, Nearest Neighbor, and classification trees.
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.
创建一个分类树(一个决策树)，并借此挖掘数据就可以确定这个人购买一辆新的M5的可能性有多大。
By creating a classification tree (a decision tree), the data can be mined to determine the likelihood of this person to buy a new M5.
对于这类数据，分类树是一种极不适合的数据挖掘模型。
然后对于挖掘到的策略和规则需要进行分类以便确定业务敏捷性，这样可能就会产生一个假的业务敏捷策略指令工作组。
The mined policies and rules will then have to be classified identifying business agility and it may be possible to derive a strawman for a working set of business policy directives.
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 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.
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.
为了描绘人类在早期文明和社会中的生活景象，考古学家挖掘、保护、研究并且将近代和古代起舞分类。
Archaeologists excavate, preserve, study, and classify artifacts of the near and distant past in order to develop a picture of how people lived in earlier cultures and societies.
InfoSphereWarehouse还包含一个TaxonomyEditor，它可以把词典条目分类为分类法树，可以供数据挖掘和OLAP使用。
InfoSphere Warehouse also includes a taxonomy Editor that categorizes dictionary entries in a taxonomy tree for use in data mining and OLAP.
部署AxisWeb服务非常繁琐，并需要深入挖掘才能对每种东西进行分类，同时Web ServicesDeploymentDescriptor (.wsdd)文件是最受支持的方法。
Deploying an Axis Web service is cumbersome and takes a bit of digging around to sort everything out, with Web Services Deployment Descriptor (.wsdd) files being the best supported method.
分类是数据挖掘领域中的一个重要研究课题。
随着数据集的数据量和维数的增加，建立高效的、适用于大型数据集的分类法已成为数据挖掘的一个挑战性问题。
With the growth of data in volume and dimensionality, it has become a very challenging problem to build a high-efficient classifier for large databases.
基于链接分类是链接挖掘的一个重要方向。
Link based classification is an important research direction in link mining.
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。
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.
数据分类是数据挖掘中一个重要的内容。
Data classification is one of important contents from Data mining.
分类是数据挖掘中的一种非常重要的方法。
Classification is one of important methods used in data mining.
分类是数据挖掘领域中一个重要的研究分支。
The Classification is an important research branch in the Data Mining domain.
目前，支持向量机在模式识别、函数逼近、数据挖掘和文本自动分类中均有很好的应用。
Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization.
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。
This paper presents a classification method for data mining based on BP neural network, and puts forward improvement ideas.
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。
The paper proposed an algorithm based on ant colony algorithm for mining classification rule from the Student Scores Management Database.
本文研究基于SLIQ的数据挖掘分类算法。
This paper studies data mining classification calculation of SLIQ.
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。
Then the method of synchronous amalgamating is chosen to implement the mining of classification rules from multiple data sources.
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