apriori是什么意思   apriori怎么读

apriori单词基本解析：

apriori变化用词：

apriori英英释义：

apriori中文词源：

apriori用法和例句：

apriori

(5)Using the Apriori algorithm to mine the association rules between the diabetes patient records, and analyzing the characteristics of the rules, and posing the approach to improve the rules;

(5)利用Apriori算法得出了糖尿病数据的关联规则，分析关联规则特点，并提出改进关联规则的方法；

apriori algorithm that is widly used in datamining processes and softwares simple implementtation have passed the tests.

(译)：Apriori算法是widly过程中使用的数据挖掘和软件简单implementtation已通过测试。

Apriori Algorithm source code integrity, and can be used directly.

(译)：Apriori算法源代码的完整性，并可以直接使用。

Apriori algorithm, Apriori association rules to achieve a complete source code can be used directly.

(译)：Apriori算法， Apriori的关联规则，以实现一个完整的源代码可以直接使用。

perl implementation of the apriori algorithm source code integrity, has been tested.

(译)：perl的执行Apriori算法源代码的完整性，已经过测试。

Apriori by fimi university complete source code can be used directly.

(译)：的Apriori的fimi大学完成的源代码可以直接使用。

Based on the analysis of Apriori algorithm from the perspectives of time complexity and memory complexity, we use an across linker to substitute the array description of the transactions database.

1前言关联规则挖掘是数据挖掘的一个方向,它反映了大量数据中项目集之间的关联或者相关联系。

2) How to discover preferential operation series segment adopting Apriori algorithm in association rules.

2) 采用关联规则中的Apriori算法获取优先工序序列段。

8 xiangping Li, Jiangping Chen, An Development algorithm of Apriori, Geo-Spatial Information Science, 2003.4.

7陈江平，李平湘，点对象的多尺度空间关联规则挖掘算法研究，计算机应用，2004年12月

improved apriori algorithm

AprioriTid优化算法

apriori parallel algorithm

Apriori并行算法

Apriori model

Apriori模型

algorithm Apriori

Apriori算法

Realization of Mining Frequent Itemsets Based on Apriori

Apriori算法中频繁项集挖掘实现研究

Application of Apriori Algorithm on Data Analyses of Forest Inventory

Apriori算法在森林资源二类调查数据分析中的应用

Apriori algorithm is the classic algorithm in the mining of associate rule.

Apriori算法是关联规则挖掘的经典算法。

An Improved Apriori Algorithm

Apriori算法的一种变形

The Improvement of Apriori Algorithm

Apriori算法的改进

Fpmine-SPF algorithm has a far taster speed in association rules mining than the widely used Apriori algorithm and has wonderful scalability.

Fpmine-SPF算法挖掘关联规则的速度远快于较长期以来广泛使用的Apriori算法，并有相当好的可伸缩性。

An optimized Apriori algorithm

一种优化的Apriori算法

One is the Maximal Forward References(MF) method, and it is like the traditional data mining methods, Apriori.

一种是采用最大向前路径(MF)方法，最后的步骤类似于传统数据挖掘中的Apriori算法。

An Apriori Estimate for the Positive Solutions of Some Fully Nonlinear Equation

一类完全非线性方程正解的先验估计

Apriori Rules on the College Students Tell Lies

一组投射大学生说谎的演绎规则集

Compared with Apriori algorithm and FP-growth algorithm, Combination Tree algorithm has better efficiency.

与Apriori算法和FP-growth算法相比，该算法具有更好的效率。

With clients consisting of Reebok Adidas SportX Nike Kaaro Biba Apriori Toyota Swatch Befree Bigrey and more Vladimir is a leading designer in today's creative design field.

与客户组成的锐步，阿迪达斯， SportX ，耐克， Kaaro ，比芭， Apriori的，丰田，斯沃琪， Befree ， Bigrey ，而且，普京是一家领先设计师在今天的创新设计领域。

In order to compare Apriori algorithm with DHP algorithm, the measurement concept of sparse transaction database is put forward.

为了对Apriori算法和DHP算法作一个较为客观全面的分析比较，文中特提出稀疏事务数据库这一度量概念。

To improve the region extraction accuracy, propose a novel method based on advanced active contour model for employing the apriori knowledge of the license plate.

为提高区域检测的正确性,利用新的改进的主动轮廓模型,利用先验知识确定精确的车牌边界。

One is to modify the Apriori algorithm to mine association rules between querying keywords and browsing websites.

二是以某些关键字为探勘的目标，来撷取前置项目组为这些关键字的关联规则。

apriori form

先天形式

apriori method

先天方法

apriori concepts

先天概念

apriori thought

先天的思维

apriori truth

先天的真理

apriori synthesis

先天的综合

apriori forms of intuition

先天直观形式

apriori logic

先天逻辑

apriori estimate

先验估计

apriori information

先验信息

apriori distribution

先验分布(概率)

apriori proposition

先验命题

apriori psychology

先验心理学

apriori probability

先验概率

apriori deduction

先验演绎

apriori knowledge

先验知识 验前知识

Application in CRM of the Algorithm Apriori of Association Rules

关联规则Apriori算法在CRM中的应用

Apriori algorithm and FP-growth algorithm are two main algorithms in mining association rules which are based on frequent itremsets.

关联规则的挖掘主要是基于频繁集的方法，相关的算法主要有Apriori算法和FP-growth算法。

It shows obviously that there are two extreme trends about economics methods used at present: one is empirical normal study, the other is apriori doctrine study.

分析表明目前的农业经济学研究中存在着两种明显的极端倾向：一种是经验式的规范研究；另一种是先验的理论教条倾向。

3.Lewis’ theory of knowledge constitution claims that: knowledge is made up of apriori concept and what is given by feeling, knowledge is the outcome of apriori concept illustrating given by feeling.

刘易斯的知识构成论提出:知识由感觉所与和先验概念两个因素构成,知识是先验概念解释感觉所与的结果。

On the other hand, risk managers have biases that cause them to prefer certain outcomes to risk assessments apriori.

另一方面，风险管理者的偏倚使其更青睐风险评价的特定结果。

Based on the apriori algorithm,using powerful functions of relation database management system and simple operation and high efficiency of SQL,an apriori algorithm based on SQL is proposed.

在Apriori算法的基础上,利用关系数据库管理系统的强大功能和SQL语言操作简单,效率高的特点,提出了基于SQL的Apriori算法。

Lastly the algorithm is applied to T25I10D10K and T25I20D100K data set and comparing with the apriori algorithm it higher the efficiency of sequence data mining.

在T25I10D10K和T25I20D100K数据集上的挖掘实验表明在本文提出的候选序列生成算法上进行挖掘比用Apriori算法进行挖掘的效率更高。

In this thesis, the definition of spatial association rule is expounded and weresearch on the Apriori algorithm of association rules, probe into several efficient methods for improving the Apriori algorithm.

在传统关联规则的Apriori算法的基础上做了改进，并提出了算法实现时的改进策略。

We will give a detailed analysis of Apriori algorithm before we present our modified Aprior algorithm.

在分析Apriori算法的基础上,提出了对Apriori算法的改进办法。

The creation in this paper is that we present an algorithm of association rules,discovery based on extension transformation and Apriori algorithm.

在原有的Apriori算法的基础上提出了在关系数据库中的可拓关联规则挖掘算法。

The paper presents a new algorithm that embodies the factor of time for mining association rules in stock linkage information based on Apriori algorithm.

在数据挖掘的模式中,关联规则是其中比较重要的一种。

Mining Association Rules Based on Apriori Algorithm and Improvement

基于Apriori算法的关联规则挖掘及改进

Optimal Bidding Strategy Based on Apriori Information under Non-base Auction

基于先验信息的无标底投标报价策略研究

Method For Paper Equivalence Based on Apriori Index

基于先验性指标的试卷等价方法

Infrared Image Car License Plate Location Method Based on Apriori Knowledge

基于先验知识的红外图像汽车牌照定位方法

Research on Mining Association Rule Based on Improved Apriori Algorithm

基于改进Apriori算法的关联规则挖掘研究

Research on Application of Data-Mining-Based Apriori algorithm in the Intrusion Detection

基于数据挖掘的Apriori算法在入侵检测中的应用

Improved Method of Apriori Algorithm Based on Matrix

基于矩阵的Apriori算法改进

It has been proven that FP-growth algorithm is better than Apriori algorithm.

实验和研究证明FP-growth算法优于Apriori算法.

The paper focus on the Apriori association rules mining algorithm ,presents an enhanced method which can effectively reduce the number of data to improve the original Apriori algorithm performance.

对Apriori关联规则挖掘算法提出了一种改进方法，使其可以有效地压缩数据规模，提高了原Apriori算法的执行效率。

For the phase of sequential pattern discovery，the paper presented the classic Apriori and the FS algorithms and proposed a new AFS algorithm which can avoid the demerit of FS algorithm.

对于序列模式挖掘，本文详细介绍了适用于Web日志频繁访问路径挖掘的类Apriori算法和FS算法，并对FS算法的不足进行了改进，提出了AFS算法。

For the positive association rule, after analyzing the character and the deficiency of the famous Apriori algorithm, we put forward an effective pruning algorithm to improve its efficiency.

对于第一种类型的关联规则，本文在分析研究了著名的提取频繁项集的先验算法的特征以及不足的基础上，提出了一种提高执行效率的剪枝算法；

researching algorithms of association rules( especially Apriori algorithm). This article brings up an efficient algorithm of association rules (named Apriori" ) in the base of Apriori"1 which exsits some problem.

对关联规则算法(特别是Apriori算法)进行深入研究，对Apriori~(-1)算法存在的问题进行了改进，提出一种高效的关联规则算法Apriori~(-2)算法。

The proposed algorithms for mining multi-level association rules such as Cumulate algorithm, ML_T2L1 algorithm are based on Apriori algorithm.

已有的多层关联规则挖掘算法如Cumulate 算法、ML-T2L1 算法,都是通过对Apriori 算法进行扩展得到的。

Compared with Apriori algorithm through examples, we draw the conclusion that two algorithms have the same results, but PrefixSpan mining algorithm is more efficient.

并通过实例比较得出,APriori算法和Prefixspan算法具有相同的挖掘结果,但Prefixspan算法的挖掘效率较高。

Application of General Genetic Algorithm(GGA) in the Improvement of Apriori Algorithm

广义遗传算法在Apriori算法改进中的应用

an apriori judgment

忆测的判断

An Optimized Apriori Algorithm for Mining Association Rules

挖掘关联规则中的一种优化的Apriori算法

Thirdly, the thesis introduces in detail DHP (Direct Hashing and Pruning) algorithm and FARM (Fast Association Rule Mining) which is an algorithm improved on the basis of Apriori and DHP.

接着，详细介绍了DHP(Direct Hashing and Pruning)算法及在Apriori算法和DHP算法基础上的快速挖掘算法FARM(Fast Association Rule Mining)；

Put forward a kind of new of TCAR analytical method based on TGIS. This method on the basis of Apriori algorithm, lead into the temporal constraints, make it is more the body the characteristic of the data of TGIS now.

提出了一种分析带时态约束条件的关联规则挖掘研究方法,该方法在Apriori算法的基础上,引入时态约束,使之更加体现TGIS数据的特性。

Improving Apriori algorith

改进的Apriori算法

Application of Improved Apriori Algorithm on Expansive Training to Cultivation of Student Quality

改进的Apriori算法在大学生素质拓展中的应用

In the paper，we option the algorithm Apriori for the candidate set generation.It is a hash-based algorithm and is especially effective for the generation of candidate set for large 2-itemsets.

文中提出基于哈希表的算法，对生成侯选项目集的过程进行了优化，尤其是对生成二维侯选项目集更是有效。

On the base of analysis of Apriori algorithm and DHP algrithm which is widely applied.

文章对关联规则发现中应用较多的Apriori算法和DHP算法进行了分析,提出了一种新的关联规则发现算法。

After understanding and analysis of association rules algorithm, this paper studies the algorithm of data mining association rules and makes some improvement to the APriori algorithm.

本文从理解关联规则算法和对其分析出发，研究数据挖掘的关联规则算法及Apriori算法的改进。

This paper proposes an approach exploiting geometric features in conjunction with apriori knowledge to search coplanar visual cues to estimate depth.

本文就侧重分析人在识别物体过程中使用的几何特征和先验知识，提出在人造几何物体图片中搜索共面线索进而实现深度信息猜测的算法。