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分类属性     
相关语句
  classify attribute
     The Research and Application of Product Classify Attribute Coding Based on CIMS
     基于CIMS的产品分类属性编码应用与研究
短句来源
     The Selection of Classify Attribute from Web Page Training-set Base on Rough Sets
     基于粗糙集的网页训练样本集的分类属性的选择
短句来源
     To select the proper classify attribute from web page training\|set is the base of many web page classify techniquis, such as decision tree, k nearest method, linear classification and SVM.
     选择合适的网页训练样本集的分类属性是网页分类时很多技术的基础 ,比如 :决策树、K邻近算法、线性分类、支持向量机等。
短句来源
     This article has analyzed characteristic and coding method of the product information,absorb the idea of the product classify attribute and use it for reference,bring forward the coding and method of the product classify attribute under the CIMS environment,it is provided with agile conformation competence and comprehensive practicability very much;
     本文分析了产品信息的特性和编码方法 ,借鉴和吸收了产品分类属性的思想 ,提出了CIMS环境下产品分类属性编码与方法 ,使分类属性的编码具有非常灵活的构造能力 ,具有广泛的实用性 ;
短句来源
     base on the principle and method,an application example is given in the paper. By the unitive product classify attribute coding and information relationship technology,realize the efficient integration of the product information.
     基于该原理 ,给出了一个应用实例 ,通过统一的产品分类属性编码和信息关联技术 ,实现产品信息的有效集成
短句来源
  categorical attribute
     This paper propose s two distance definitions for attribute-mixed dataset,and generalizes dissimilarity to multi-function of distance and cluster size,the new distance and dissimilarity definitions make existed clustering algorithms for numerical attribute or categorical attribute can be used to attribute-mixed dataset.
     该文针对混合属性数据集,提出两种距离定义,将差异性度量推广成为距离、类大小等因素的多元函数,使得原来只适用于数值属性或分类属性数据的聚类算法可用于混合属性数据。
短句来源
     Considering the size of quantitative attribute values and categorical attribute values in databases, the paper presents two quantitative association rules mining methods considering privacy-preserving respectively, one bases on boolean association rules, the other bases on partially transform measure.
     根据数据库中量化属性值和分类属性值数量的不同,分别提出了基于布尔关联规则的量化关联规则隐私保持挖掘方法和基于部分变换机制的量化关联规则隐私保持挖掘方法。
短句来源
     ROCK,proposed by Sudipno Guha et al in 1999,is a well known,robust,categorical attribute oriented clustering algorithm. The main contribution of ROCK is the introduction of a novel concept called "common neighbors"(links) as similarity measure between a pair of data points. Compared with traditional distance-based approaches,links capture global information over the whole data set rather than local information between two data points.
     ROCK是Sudipno Guha等1999年提出的一个著名的面向分类属性数据的聚类算法,其突出贡献是采用公共近邻(链接)数的全局信息作为评价数据点间相关性的度量标准,而不是传统的基于两点间距离的局部度量函数.
短句来源
  categorical attributes
     The fuzzy K-Modes clustering algorithm is an effective method for clustering the data with categorical attributes.
     模糊K-Modes聚类算法是对具有分类属性的数据进行聚类的一种有效的算法。
短句来源
     The Study of Clustering Data with Categorical Attributes in Data Mining
     数据挖掘中分类属性数据聚类研究
短句来源
     Similarity measurement is the key to solving the clustering problem, while similarity of categorical attributes can’be measured by Euclidean distance.
     相似性的度量是解决聚类问题的关键,而分类属性的相似性无法用欧几里德(Euclidean)距离来度量.
短句来源
     The measure of similarity is the key to solve clustering problem. Aiming to the shortage of traditional method, Information entropy theory is introduced to solve intrusion detection clustering problem that includes categorical attributes.
     相似性的度量是解决聚类问题的关键,根据传统方法的不足,引入信息熵理论来解决含有分类属性的入侵检测聚类问题。
短句来源
     This paper discusses how to deal with the clustering problem with categorical attributes by means of the theory of similarity coefficients and the theory of entropy, and emphatically studies the equivalence of the two similarity measures in resolving the clustering problem for intrusion detection.
     探讨用相似性系数理论和信息熵理论两种方法去解决含有分类属性的聚类问题,并重点对这两种相似性度量方法解决入侵检测聚类问题时的等效性进行了研究。
短句来源
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  category attributes
     When a group of objects move “from top to bottom”along a given device of a Haffman tree shape,they will besorted into different subgroups according to their category attributes.
     如果一组客体沿形如 Haffman 树状的给定装置从顶部到底部运动,那未它们将按其分类属性被分成不同的类别。
短句来源
     last, we compare the system use thesaurus which contains category attributes with the system use thesaurus which neglects category attributes, the experiment demonstrates that category attributes and classification contributes to the efficiency of Chinese input method.
     最后通过对比使用分类属性词库系统和不使用分类属性词库系统的实验, 给出了分类对输入法系统的影响,实验结果表明类别划分和分类对提高输入法的效率有积极的作用。

 

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      categorical attribute
    Yet another application would be clustering categorical data, where each categorical attribute could be viewed as a clustering of the data set.
          
    After the data were partitioned based on a categorical attribute A5; the model selected are shown in Table 6.
          
    A leaf of the tree specifies the expected value of the categorical attribute for the records described by the path from the root to that leaf.
          
    And secondly, missing values are treated as special categorical attribute values.
          
    As such, each continuous attribute is transformed to a categorical attribute with 4 distinct values.
          
    更多          
      category attribute
    These implementations use rudimentary metadata representing measurement-theoretical and category attribute information to support error checking of data derivations common in research and reference using social science data.
          
    Let dt be a terminal attribute, dp a property attribute, and dc a category attribute of a common dimension.
          
    This data includes least count for numeric attributes and category attribute trees and the auxiliary data required for key derivation.
          
      categorical attributes
    In this paper, we formulate the problem of summarization of a data set of transactions with categorical attributes as an optimization problem involving two objective functions - compaction gain and information loss.
          
    The k-prototypes algorithm, through the definition of a combined dissimilarity measure, further integrates the k-means and k-modes algorithms to allow for clustering objects described by mixed numeric and categorical attributes.
          
    Categorical attributes are typically ignored or incorrectly modeled by existing approaches, resulting in a significant loss of information.
          
    We report on a new, efficient encoding for the data cube, which results in a drastic speed-up of OLAP queries that aggregate along any combination of dimensions over numerical and categorical attributes.
          
    Identifier attributes-very high-dimensional categorical attributes such as particular product ids or people's names-rarely are incorporated in statistical modeling.
          
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