数值型数据

通过分析互联网质量异常的现象，提出了模糊度量Web资源质量的方法，并将互联网资源质量状况转化为计算机能识别的数值型数据。

Fuzzy measure of web source quality is presented by the analysis of Internet quality anomalies , and the quality of Internet source is transformed to numeric data which can be identified by the computers .

本文首先对肝脏31P磁共振波谱图像进行预处理，将波谱曲线转化为可利用的数值型数据，从而建立新的数据样本集。

This paper firstly pre-processes the hepatic 31P MRS pictures , and changes the curves of the pictures into numeric and available data , so the new subset of data sample is established .

同时，设计出了FARM模糊动作关联规则算法，对企业关系价值真实数值型数据进行挖掘，并挖掘出提升企业关系价值的主要规则。

Meanwhile , FARM algorithm is designed to mine the real numerical data of enterprise relationship value .

K均值算法是最常见的聚类方法，因其在处理大型数据集时的高效性而闻名，但缺点是只能处理数值型数据。

The K-Means algorithm is the most frequently used clustering method and is promising for its efficiency in processing large data sets .

k-means算法对于处理数值型数据有好的聚类效果，但是不能处理常见的字符型数据。

K-means algorithm shows good in processing numerical data and has good clustering results , while it can not handle character data .

最后，本文分别对机器学习数据库中的Iris，Wine等七组数值型数据、非数值型数据Balloon数据以及随机生成的含有噪音点的人工数据集进行了聚类实验。

Finally , the paper carries out the clustering experiments to Iris , Wine , and etc. & even groups of numerical date , non-numeric data Balloon data of the machine learning database and randomly generated artificial data sets with noise point .

利用Excel进行日常事务管理的人们，经常会遇到在Excel中无法将文本型数据转换为数值型数据的一些问题，从而导致无法正常进行数据分析、数据运算等工作。

The people , who deal with the daily business by using Excel , often meet some unsolvable problems of translating textual data into numerical data , so that they can 't normally do some works , such as , data analyzing , data arithmetic .

多数数值型数据不能用整数表示。

Most numerical data can 't be represented as integers .

基于数值型数据的模糊规则快速挖掘方法

Fast Generation Method of Fuzzy Rules from Numerical Data

从压缩的角度考虑，数据分为数值型数据与非数值型数据。

From the point of view of compression , data can be classified as non-numerical and numerical data .

针对知识产权数据库系统中的非数值型数据的特点，本文提出了一种基于相似函数的关系数据库水印算法。

A watermarking relational database algorithm based on similar function is proposed for non-numerical data in intellectual property relational database .

通过云变换实现了泛概念树中叶结点的自动生成，并自动构造数值型数据的泛概念树。

Cloud transform is realized to automatically produce the basic numerical concepts as the leaf nodes in pan concept tree .

现有的聚类算法处理低维数据有良好的效果，同时高维数值型数据的聚类分析也取得了一定的成就。

Existing clustering algorithm processing low-dimensional dataset has a good effect , while the high-dimensional cluster analysis of numerical data has also made certain achievements .

对数值型数据保持顺序加密方法进行了分析，在此基础上提出了一种在关系数据库中针对字符数据的保序加密方法。

In this paper the order preserving encryption for numeric data is analyzed . An order preserving encryption method for character data in relational databases is proposed .

字符串数据长度的变化或数值型数据精度和等级的变化也表明在数据的表示、验证和使用上存在潜在的问题。

Variations in length for string data or in precision and scale for numeric data also point to potential issues in data presentation , validation , and usage .

然后，在数据分类器的实现中，论述了数据的概念层次提取和管理，并对数值型数据给出了一个自动提取概念层次算法；

In the implementation of data classifier , we describe extraction and management of conceptual hierarchy for data , also design an automatic extraction algorithm for numeric data .

在电信运营商的数据库中存在着大量的数值型数据，进行数量关联规则挖掘的难点之一就是数值区间离散化问题。

There are a mass of data of numerical value type in telecom companies ' database . How to reasonably partition domain values is very important in quantitative association rules mining .

决策树方法不仅能够直接体现数据的特点，便于理解，具有较好的分类预测能力，能方便提取决策规则，而且擅长处理非数值型数据。

Decision tree can directly reflect the features , easy to understand , has better classification of the predictive power , easy extracting decision rules , and is good at dealing with non-numeric data .

针对数值型数据能准确反应现实世界，但难以理解的问题，为了从数值型数据中挖掘出易于理解的知识，提出了基于数值型数据的模糊规则快速挖掘方法。

To the problem that the numerical data reflecting the real world is difficult to be understood , a fast generation method of fuzzy rules is presented in order to extract the linguistic knowledge from numerical data .

在分析数值型数据的保序加密方法的基础上，提出了一种针对字符数据的模糊匹配加密方法，阐述了其加密原理、过程、算法特性和鲁棒性。

Based on the order preserving encryption method for numeric data , this paper proposes a fuzzy match encryption method for character data in the database . Encryption principle , process , algorithm property and robustness analysis are described .

然而，随着科学技术的不断发展，数据规模不断的扩大，研究数据的属性也不单单是数值型数据，出现了分类数据和混合数据。

However , as the continuous development of science and technology , together with constantly expanding of the size of the data , there has been categorical data and mixed data , and the studies is not just limited to numerical data .

数据挖掘中的关联规则主要是从大量的数据中，探讨数据项目之间的关联性，它多应用于二元的数据分析上，对于数值型数据的处理上，缺乏弹性。

The association rule of the data mining technologies is to explore the relevance among data items which are stored in databases . It is often used in the analysis of binary data . It lacks of flexibility in dealing with numerical data .

在密文数据的查询方面，对于字符型数据采用两阶段查询算法；对于数值型数据采用基于B~+树的查询算法，与传统的查询算法相比，以上两种改进的查询算法的效率都有所提高。

Cipher text data in the inquiries , the character data using two-phase query algorithm ; numerical data for the B ~ + tree-based query algorithm , and compared to the traditional search algorithms , both to improve the efficiency of search algorithms have improved .

但是要在连续数值型的数据中挖掘出所需要的专家规则目前还没有快速有效的方法。

But mining the expert rule in the continuously numerical data that needs not to have the fast valid method at present .

但传统的关联规则挖掘算法存在耗时长以及规则冗余的问题，并且无法直接应用于分布式的数值型医疗数据的挖掘。

But traditional algorithms of association rules mining have disadvantages of time-consuming and generate redundant rules , which cannot be used to mine the distributed and numeric medical data directly .

对于数值型样本数据，首先采用模糊聚类生成模糊规则库，然后运用粗糙集理论对样本属性进行约简，删除冗余规则，即可得到精简的模糊规则库，以方便进行分类决策。

Firstly , generates fuzzy rules base using fuzzy clustering from numerical sample dates , and then simplifies the sample attributions using rough set theory , deletes the redundant rules , and gets the simplified fuzzy rules base , in order to make classification decision conveniently .

基于遗传算法的非数值型软件测试数据自动生成方法研究

Study on the Method of Automatic Test Generation of Non-Numeric Data Based on Genetic Algorithms

同时，将录入的数值型电解铝数据转换成标称变量型数据，开发基于标称变量的聚类方法分析方法、展示电解槽生产数据的内在规律。

At the same time , will the numeric aluminum data into a nominal variable data , using the nominal variables based on clustering method analysis , show the inherent law of the production data .

模糊KPrototypes（FKP）算法融合了kmeans和kmodes对数值型和符号型数据的处理方法，适合于混合类型数据的聚类分析。

Fuzzy K-Prototypes ( FKP ) algorithm integrating K-Means and K-Modes algorithm is suited for clustering mixed numeric and categorical valued data .

在归纳现有关联规则研究的基础上提出了事务间数值型关联规则的数据挖掘问题，并对该问题进行了定义。

Based on the summarization of data mining research , the problem of mining inter-transactional quantitative association rules are brought forward and defined in this paper .