最后给出了一个完整的数据挖掘模型。
提出了一种基于聚类和粗糙集的数据挖掘模型。
We propose a data mining model based on clustering and rough set.
运行数据挖掘模型要比将数据载入模型简单得多。
It's much easier to run the data mining model than to load the data into it.
对于这类数据，分类树是一种极不适合的数据挖掘模型。
还给出了模拟例子说明如何建立和运用这种数据挖掘模型。
Lastly, a simulated examples on how to create and apply this model is given.
作为对数据挖掘模型的验证，介绍了供水公司水费收缴预警系统。
Oilfield water supplying payment warning system for verifying the data mining model is also described.
在数据挖掘阶段，论文首先对数据挖掘模型中的数据进行属性分类。
In the data mining stage, the paper first the data in the data mining model attribute classification.
导出模块则相反地读取数据挖掘模型相关信息，输出pmml文档。
Contrarily, the output module accepts information of mining model and outputs the PMML document.
针对选煤厂的特点，建立了水平式数据挖掘模型和垂直式数据挖掘模型。
Based on the characteristics of coal preparation plant, horizontal data mining model and vertical data mining model were built in this paper.
通过对预测结果同实际发生事件的对比，表明数据挖掘模型是有效的。'）；
Through to forecast the result with the real time contrast, indicated the data mining model is effective.
在增量式动态数据库中，提出了相容性和不相容性决策系统的数据挖掘模型。
In the dynamic increment database, data mining models of consistent and inconsistent decision system are formulated.
并按照ID 3算法建立了决策树数据挖掘模型的例子，用于分析评估客户资信。
A decision tree by using for ID3 algorithm has been established, which evaluates the customer's credit.
与传统的数据挖掘方法相比较，区间值聚类的数据挖掘模型更加高效、准确、符合实际。
By comparison with the traditional method for data mining, this method is more effective, more accurate, and more accordant to practice.
因此，人们期望能够在一个开放式环境下实现对数据挖掘模型和挖掘组件的集成和重用。
So, it is hoped that data mining models and mining modules can be integrated and reused in an open environment.
针对传统的基于粗糙集理论的数据挖掘模型存在不实用的特点，提出了一种改进的数据挖掘模型。
Finally aims at the tradition to have the impractical characteristic, proposed data mining model based on the rough set theory.
介绍了基于案例推理的数据挖掘技术及其实现方法，以此为依据建立体检信息分析的数据挖掘模型。
Introduced the case-based reasoning of data mining technique and the realized method, took this as the basis to build up the data mining model of the body detection information analysis system.
这样得到的XML数据挖掘模型存储在数据库中，可以通过SQL/XQuery进行访问。
The resulting XML data mining model is stored in the database and can be accessed through SQL/XQuery.
设计模式包含用于选择单个数据挖掘模型和输入表的图形设计图面，同时还包含用于指定预测查询的网格。
Design mode includes a graphical design surface used for selecting a single data mining model and input table, and a grid used for specifying the prediction query.
是个开源的数据挖掘平台，通过一个用户友好的工作流接口提供通用数据挖掘模型的构建和数据清洗功能。
AlphaMiner is an open source data mining platform that offers versatile data mining model building and data cleansing features with an user friendly workflow interface.
在遥感图像数据挖掘模型与实现方面，提出了遥感图像数据挖掘模型结构。基于该模型进行创建、训练和预测。
As for the RS image data mining model (RSDMM) and its implements, the RSDMM's architecture and its creation, training, and prediction is discussed.
采用了属性构造法进行数据预处理，建立了数据挖掘模型，实现了关联规则算法，并对挖掘结果进行解释与分析。
A model of data mining is set up after preparation of data by means of attribute structure, and association rule algorithms are carried out. the data mining result is explained and analysed.
最后，本文探讨了第一个数据挖掘模型：回归模型(特别是线性回归多变量模型)，另外还展示了如何在WEKA中使用它。
Finally, this article discussed the first data-mining model, the regression model (specifically, the linear regression multi-variable model), and showed how to use it in WEKA.
本文提出灰色系统的理论与方法在物流行业的应用，针对物流企业管理决策的实际问题建立基于灰色系统理论的数据挖掘模型。
This article introduces grey theory into logistics trade, and builds data mining model based on grey theory to solve the practical problem in logistics enterprises' management and decision.
但是目前基于概念格的数据挖掘模型都是针对“静态”数据库，属性值只是从单层次上的数据中取值，缺少了信息粒度的变化。
While the existing models based on concept lattice aim at the static database and the attribute value is just from the single level, lacking of the transformation of granularity.
面对数据的海洋，传统的单机串行算法己经不能适应快速、实时的知识需求，研究面向多机、并行、分布式的数据挖掘模型越来越重要。
The traditional serial algorithm can't do work well for the data ocean quickly and correctly, it also important to research the parallel algorithm.
本文提出一种基于粗糙集理论的数据挖掘模型，从实际数据出发，运用不同简化层次的算法，导出每个层次上的信息集，最后得到规则集。
This paper present a model of data mining based on rough set, from apply various reductive level algorithms on practical data to elicit information set, and get a rules set eventually.
DM技术与OLAP技术是电力营销决策支持系统中的关键数据分析技术，二者有机结合构成的多维数据挖掘模型能提高数据分析的效果和性能。
The DM and OLAP are the critical techniques of data analysis, the multi dimensional data mining model combining both techniques can enhance the performance and effects of data analysis.
灰色数据挖掘模型在物流企业的管理决策问题中的应用证明了基于灰色系统理论的灰色预测和聚类模型是有效的、具有实用价值的数据挖掘模型。
The application of grey data mining model in the management and decision of logistics enterprises has proved that the grey forecasting model and clustering model is effective and of practical value.
灰色数据挖掘模型在物流企业的管理决策问题中的应用证明了基于灰色系统理论的灰色预测和聚类模型是有效的、具有实用价值的数据挖掘模型。
The application of grey data mining model in the management and decision of logistics enterprises has proved that the grey forecasting model and clustering model is effective and of practical value.
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