分类数据

This dissertation, in the light of the limitations of existed methods, suggest an algorithm based on Conception Hierarchy Tree for data mining, constructing tree from bottom to top through the method of variedly dividing interval and realizing conception hierarchy construction and conception exaltation isochronously.

本文针对已有数据分类算法的不足，采用&变间隔分割初始区间&和&概念层次构建与概念提升同步&的方式&自底向上&地构建概念层次树，提出并实现了基于概念层次树的数据挖掘改进算法。

With the development of the fuzzy math,people used to accurate mathematical method to study fuzzy problem and unify accurate method and fuzzy mothed.

随着近年来数据挖掘技术的发展，聚类分析越来越多地用于大量的未知类别数据的分类。

Data from a histological and ultrastructural study of a case of VT dilation are reported, and the results are compared with those obtained from the VT of 5 fetuses to explain the nosological aspects of nontumoral VT lesions.

我们的文章就是报道了2个VT老年病例。通过提供其中一个VT病例的组织学和超声影像检查的数据，并与5例婴幼儿VT的检查数据向比较，从而解释这种非肿瘤性VT病灶的疾病分类。

Association rule is an important content in data mining, efficient arithmetic is the most important part of data-mining 昺odel, especially when facing the complicated and various demands, it is necessary to propose characteristic and complementary arithmetic according to different factors. The paper analyses elaborately the idea of association rule mining arithmetic based on constraints, studies the classes of constraints in order to confirm its utility. The arithmetic aiming at united variable constraints improvement strategy and exchange of complication aggregation constraints has been designed, the practice has proved that it is effective.

关联规则是数据挖掘研究的重要内容，高效的算法是数据挖掘的重要组成部分，而且面对复杂的多方面的需求，应提供针对各种因素的各具特色的互补的多种算法，本文详尽地研究了基于约束的关联规则挖掘算法的思想，深入地研究了约束的分类、确定其可利用的性质，在此基础上提出了针对联合约束中前驱和后继重叠时的改进策略和复杂聚集约束的转换方法。

Melissa Data — A directory of complete demographic data, sortable by ZIP code.

雪数据名录完成人口统计数据，被邮编的分类。

Based on the properties of hyperspectral image data, effective classification algorithms for extracting most information of groundcover types from hyperspectral image data are studied in this thesis.

本文针对高光谱图像数据的特性，研究了如何从高光谱数据中提取出地物类型的丰富信息以进行有效的分类。

The DTM for automatic-design of thruway was put forward by Prof. Miller in 1956. Since then , the DEM is used for design of various circuit diagram, and for account of area, cubage, gradient of various project, and for estimating visibility from point to point; for rendering contour, grade-graph, aspect-graph, solid model; for making orthographic image and repair map in the Topography; for assistant data to classify in the Remote Sensing; as basic data in the GIS, for analysis and layout actuality of using soil, for disaster prediction; for navigation, guiding missile in the military affairs.

美国麻省理工学院Miller教授为了高速公路的自动设计于1956年提出了数字地面模型的概念后，DEM被用于各种线路的设计及各种工程的面积、体积、坡度的计算，任意两点间可视性判断及绘制任意断面图；在测绘中被用于绘制等高线、坡度坡向图、立体透视图，制作正射影像图与地图的修测；在遥感中可作为分类的辅助数据；它是地理信息系统的基础数据，可用于土地利用现状的分析、合理规划及洪水险情预报等；在军事上可用于导航及导弹制导；在工业上可利用数字表面模型DSM或数字物体模型绘制出表面结构复杂的物体的形状[2]。

Customer Relationship Management that can supply customers resources and involved data analysis is the key, But a huge amount of data prevent us from discovering valuable customer mode, so the research of knowledge discovering system applied in Customer Relationship Management to class reasonably customers is very significative. Now, there are many methods classing customers applied in Customer Relationship Management.

能够提供客户资源及相关数据分析的客户关系管理系统就成为焦点，但是客户关系管理系统中庞大的数据量阻碍了我们从中发现有价值的客户模式，因此研究适用于客户关系管理的知识发现系统，从而合理地实现客户分类，具有十分重要的理论意义和实用价值。

This paper proposes a novel transfer-learning algorithm called DRTAT,which dynamically regroups the primary training data sets and eliminates the redundancy data timely,then makes classifiers ensemble.

提出了一种新的迁移学习方法DRTAT，对原训练数据进行动态分割重组，适时地淘汰冗余数据，并进行分类器的集成。

For example , you can define formatting for multiple levels of data , there are multiple levels of subtotals possible in a PivotTable , etc .

譬如，你可以在数据透视表中定义多种级别数据的格式，也可以设置尽可能的多种级别的分类汇总。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。