categorical data
英 [ˌkætəˈɡɒrɪkl ˈdeɪtə]
美 [ˌkætəˈɡɔːrɪkl ˈdeɪtə]
分类数据；类型资料；（数）范畴数据
双语例句
- Concerning the categorical characteristics of spatial data, a rule-based spatial co-location method in categorical data is introduced.
针对空间分类数据的特性，提出一种空间分类数据同位规则挖掘算法。 - Objective The statistical method for repeated measures categorical data analysis was introduced and applied to clinical trials.
目的介绍分类数据重复测量资料的统计分析及其在临床试验中的应用。 - Basic to any analysis of categorical data is a consideration of how the data was collected.
任何范畴数据分析的基础在于考虑数据是怎样收集的。 - Categorical data in its broadest sense is simply a collection of values of discrete variable obtained from a sample of individuals of objects.
范畴数据在广义上就是一批得自于个体或对像样本的离散变量值。 - The Research on Clustering Algorithm for Categorical Data Using Quantum Mechanics
基于量子机制的分类属性数据聚类算法研究 - They may also be asked to conduct categorical data analysis, robust estimation or survival analysis.
他们也可能会要求进行分类数据分析，稳健估计或生存分析。 - Studies on Clustering Algorithm for Categorical Data Based on Graph Theory
基于图论的符号型数据聚类算法研究 - Aim: To summarize the trend test analysis methods for two-way ordinal categorical data.
前言：目的：探讨双向有序分类数据相关的趋势检验方法。 - Objective To explore the ROC analysis methods for repeated ordinal categorical data in diagnostic test.
目的探讨诊断试验中重复有序分类测量数据的ROC分析方法。 - The influencing factors of feat technique in hygiene were investigated in Sichuan with the method of the stratified sampling and the categorical data analysis.
采用分层抽样方法和分类资料统计方法，开展四川省农村卫生适宜技术推广影响因素调查研究。 - Analysis of the ordered categorical data in cross-over trial using generalized estimating equation
广义估计方程在交叉设计等级资料分析中的应用 - Secondly, a new algorithm based on the idea of coverage density is proposed for clustering categorical data.
本文针对类别数据的特点，提出了一种基于覆盖率的类别数据聚类算法CCCD。 - A New Fuzzy Clustering Algorithm of Categorical Data Set Based on the Kernel Method
基于核方法的分类型属性数据集模糊聚类算法 - A Clustering Algorithm for Categorical Data and its Application
一种可分类数据的聚类算法及其应用 - Rule-based outlier mining approach in categorical data
基于规则的分类数据离群挖掘方法研究 - The statistical methods for categorical data have been discussed with examples in clinical papers.
以几篇临床论文实例讨论分类断据的统计方法。 - This paper presents a Random Projected Clustering algorithm ( RanPC) for categorical data.
介绍了一种适用于符号型高维数据的随机投影聚类算法。 - Clustering Algorithm for Boolean and Categorical Data
聚类布尔和分类数据 - A Preliminary Study of a New Method for Categorical Data Analysis in Competition and Training
比赛与训练中定性资料分析的新方法初探 - Study on Storage Structure of Spatial Data and Categorical Data in GIS
GIS空间数据与属性数据的存储结构研究 - The Statistical Analysis with Repeated Measurement of Categorical Data
重复测量分类数据的分析 - These algorithms can also be used on categorical data if the data were preprocessed.
对于分类属性数据，在进行变换后，也能用这三种聚类方法产生多隶属聚类。 - Categorical data appear often in repeated measurements problems.
重复测量问题常常涉及到分类数据。 - Furthermore, the application of GEE1 and Multilevel model could be extended to quantitative data and categorical data, while ZIP model is only suitable to binary data.
GEE1和多水平模型可以推广到计量资料和分类资料的分析，ZIP模型只能分析两分类的数据； - The clustering algorithm of numerical data cannot be easily applied to categorical data with its lack of inherent geometric model.
由于分类属性数据缺少固定的几何模型，不能将原有的数值属性数据聚类算法应用于分类属性数据中。 - This paper focuses on the simple Bayesian approach which is widely used for estimating and replacing missing categorical data.
本文着重研究了复杂值补全法中广泛应用的朴素贝叶斯补全缺失数据的方法。 - The research results in the paper will provide new methods and techniques for cluster analysis of categorical data, and have applicational values in some domains such as data mining and knowledge discovery.
本文的研究为符号属性数据的聚类分析提供了新方法与新技术，在数据挖掘和知识发现等领域有着较的应用价值。 - Same categorical data priority question, sleep machine-made question.
同类型数据的优先权问题，睡眠机制问题。 - Categorical data between groups with Chi-Square test, ranked data between groups with Wilcoxon rank sum test.
分类资料组间比较采用χ2检验，等级资料组间比较采用Wilcoxon秩和检验。 - 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.
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。